Personalized Cancer Therapy on Molecular Basis: History
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Personalized cancer therapy is a treatment strategy that takes into account the molecular profile of patients in order to stratify them into groups that are more likely to benefit from different therapeutic approaches. Cancer is the second leading cause of death globally. One of the main hallmarks in cancer is the functional deregulation of crucial molecular pathways via driver genetic events that lead to abnormal gene expression, giving cells a selective growth advantage. Driver events are defined as mutations, fusions and copy number alterations that are causally implicated in oncogenesis. Molecular analysis on tissues that have originated from a wide range of anatomical areas has shown that mutations in different members of several pathways are implicated in different cancer types.

  • molecular oncology
  • precision medicine
  • tumor

1. Personalized Therapeutic Strategies Require Understanding of the Underlying Signaling Pathways’ Mechanisms

Cancer can be regarded as a collection of diseases, all of which share a common feature; the deregulation of key signaling cascades that leads to uncontrolled cellular proliferation [1]. Malignancies arise from alterations in the DNA sequence of genes, as well as from epigenetic changes [2][3][4][5][6]. Both changes induce the activation of oncogenes or the inactivation of tumor-suppressor genes, leading to evasion of growth suppressor function, resistance to cell death (apoptosis), uncontrolled cell cycle, immune evasion as well as increased invasive and metastatic potential [7]. Cancer diagnosis is becoming more reliant on the characterization of mutated pathways that can provide vital information to the separation and clustering of cancer types [8]. Several signaling cascades, including the b-catenin/Wnt, RTK/RAS, p53 and Sonic Hedgehog (SHH) pathways, are linked to cancer formation due to genetic variations that often occur in the respective genes [9][10]. Identification of mutations in genes implicated in such pathways has the potential to reveal the causative driver events of carcinogenesis [11]; it therefore constitutes a topic of paramount importance in precision medicine and for the development of efficient tailor-made drug therapies targeting each cancer type at the molecular level.

2. The p53 Pathway

Components of the p53 pathway function cooperatively to ensure that the cell will respond effectively against a variety of stress signals that threaten cellular homeostasis and genomic integrity. In this process, p53 target genes trigger several pathways linked to cancer, such as cell cycle arrest, senescence or apoptosis, blood vessel formation and the regulation of metabolism [12][13][14][15][16]. The importance of TP53 in cancer development is evident by the fact that it occupies the first place in the ranking of genes found to be most frequently altered in cancer [17][18]. Indeed, the number of cancer types/subtypes where p53 pathway is likely not perturbed is very small (e.g., uveal melanoma) (Figure 1). In the majority of cancer types, more than 30% of the samples examined harbored driver mutations in at least one key gene of this pathway, while in some cases this percentage exceeded 90% (e.g., esophageal squamous cell carcinoma). Even though there is a high number of cancers that bear a variant in one or more components of the p53 pathway, the affected components are specific to three genes in this pathway. It was found that among those patients, 93.66% had a driver mutation in TP53, whereas CDKN2A and ATM genes were affected in 7.71% and 6.27% respectively, dictating the simultaneous presence of some of these mutations in a number of cases. TP53 driver mutations can be located in virtually any region of the gene, thus affecting the ability of the p53 protein to appropriately interact with either its protein effectors or the DNA [19]. According to the analysis, arginine residues on positions 273, 248 and 175, all of which belong to the DNA-binding domain [20], are the most frequently mutated, representing 7.06%, 5.87% and 4.41% of patients that have an affected TP53 gene, respectively. R273 variants have been associated with an increased proliferative and invasive potential, which for R273H, are induced by the inhibition of tumor suppressor KLF6 [21][22]. Similar effects seem to take place when a R248 mutant is present, but this particular mutation leads to a robust binding of certain variants—mainly the mutp53R248Q—to the STAT3 protein, and to the subsequent activation of the latter [23][24]. The R175H variant, on the other hand, is associated with a radical change in p53 conformation which triggers the transactivation of a panel of genes and results in elevated c-met protein levels and to the induction of tumor invasion, among other events [25][26].
Figure 1. Alteration rate of 27 signaling pathways across 36 cancer types/subtypes. For this analysis, 10,066 tumor samples of primary origin and with available mutational profiles were examined for the presence of somatic driver mutations in the 204 genes of interest. Calculations were performed by taking into account all the available mutationally profiled primary tumor samples of the cBioPortal selected studies (10,066 samples) instead of the driver event-harboring mutationally profiled primary tumor samples (7915 samples). If for a selected cancer type there were x mutationally profiled primary tumor samples available in the cBioPortal selected ones, then, y samples would bear at least one driver event in at least one of the 204 genes of interest and z samples would harbor driver events in genes participating in a selected signaling pathway. The corresponding driver mutational rate for this cancer type-signaling pathway pair is calculated as (z/x) × 100. Here, only cancer types/subtypes that entail more than 50 analyzed samples are shown. From left to right, signaling pathways are displayed in descending order of total mutational frequency. n: number of samples examined.
In addition to missense mutations and other mutation types, the CDKN2A gene is frequently affected by nonsense mutations, in line with the analysis, which demonstrates that R80*, R58*, W110*, E120*, Y44* and E88* together constitute almost a third of cancer cases that harbor a defective CDKN2A gene. Such alterations shut down one of the cell cycle’s checkpoints, as they force the p16INK4a protein to lose its Cdk-binding ability, thereby being unable to prevent the G1/S transition [27][28][29]. From the remaining two thirds of cases, an aberrant splicing involving the D153 residue appears in 5.16% of all CDKN2A affected cancer patients. Changes in this position may inactivate both CDKN2A gene products, i.e., p16INK4a and p14ARF, leading to loss of cell cycle control via both pRB and p53 inactivation [28].
Factors upstream of p53 are also affected and, along with the ATM kinase, play a vital role in the activation of p53 in response to DNA damage [30][31][32][33][34][35][36]. In the dataset, non-sense mutations leading to premature truncated forms of the ATM protein product represented more than one third of all ATM mutated cases, with R250* being the main representative. In these cases, the final gene product loses its functionality as a main DNA damage sensor, either partially or completely, thus increasing the vulnerability of the cell to malignant transformation [37]. The analysis has also revealed that R337C/H are the most common cancer-related missense mutations in the ATM gene, accounting together for 7.94% of all ATM variant carriers. Although these mutations have been documented in cancer patients [38][39], to the best of the knowledge their functional impact has not been elucidated yet [40].
As expected, the dynamic presence of these genes on the mutational cancer map, has made the p53 pathway—and especially the TP53 component—an attractive therapeutic target. Among a plethora of p53-targeting strategies, the most promising fall into one of the following categories: (i) restoring the function of p53 protein or (ii) impeding the interaction between p53 and its main negative regulator, the MDM2 E3 ubiquitin ligase [17][41][42]. In this context, eprenetapopt (APR-246), a mutant-p53 conformation resetting agent, is probably the most promising compound [43] and the only therapy of this category that is currently being tested in a phase III clinical trial (NCT03745716); on the other hand, a phase III trial of idasanutlin (NCT02545283), another emerging MDM2 inhibitor, was recently terminated due to low efficacy. The results of such clinical trials, as well as the efforts to improve the properties of the relevant compounds are highly anticipated. Apart from p53, there are four FDA approved anticancer drugs targeting CDKN2A signaling: abemaciclib, palbociclib, ribociclib and trilaciclib [44][45][46][47]. All these therapeutic agents act as CDK4/6 inhibitors, aiming to restore the inactivated CDKN2A [48][49]. However, it has been noted that p16ΙΝΚ4a loss does not necessarily predict response to CDK4/6 inhibitors [50][51][52][53][54]. The rationale behind ATM deficient-related therapeutic approaches however, is to cause synthetic lethality. There is evidence that this is feasible by further weakening DNA repair mechanisms via administration of appropriate inhibitors, mainly PARP and ATR inhibitors, either alone or in combination [55][56][57]. Ongoing clinical trials will validate the potential of preliminary preclinical trial results and their translation into clinical practice.

3. The RTK-RAS Pathway

RTK-RAS is probably the most thoroughly studied cancer-related signaling pathway. Its involvement in a multitude of crucial physiological processes, such as cell growth, proliferation, differentiation, angiogenesis, integrin signaling and cell migration [58][59][60], among many others, makes it clear that deregulation of this pathway can facilitate both tumor initiation and tumor progression. Indeed, the analysis showed that in 12 of 36 cancer types and subtypes examined, more than 30% of patients carried driver mutations in RTK-RAS pathway genes, with this percentage rising above 80% in papillary thyroid cancer, cutaneous melanoma and mucinous adenocarcinoma of the colon and rectum. On the other hand, as with the p53 pathway, no uveal melanoma patient was found to be affected (Figure 1). The predominantly mutated genes involved in this pathway, i.e., KRAS, BRAF and NF1, were found mutated in 26.05%, 17.06% and 13.06% of RTK-RAS perturbed cases respectively, while additional mutations in all cancer-related receptor tyrosine kinase-encoding genes represented 33.2% of all mutations. In descending order of mutational frequency, these were as follows: EGFR, ERBB2, FGFR3, FLT3, FGFR2, ERBB3, RET, KIT, MET, ERBB4, PDGFRA, ALK, FGFR1, NTRK3, NTRK1, ROS1, NTRK2, IGF1R and FGFR4.
Ιn the cohort, it was ascertained that KRAS is almost exclusively mutated (missense mutations) on the G12, G13, Q61 and A146 residues, corresponding to more than 95% of all cases (75.41%, 11.68%, 5.84% and 3.67%, respectively). Mutants of codon 12, 13 and 61 decrease the GTP-hydrolysis rate, with mutants of codon 12 and 16 also being capable of increasing the rate of GDP-exchange [61][62], while mutants of codon 146 act mainly through the second mechanism [63][64]. Both mechanisms lead to increased levels of the activated GTP-bound form of the KRAS protein, resulting in uncontrolled mitogenic processes via a constitutively active signal transduction [62][65].
V600 is the most prevalent mutated codon of the BRAF gene, occurring in 81.74% of all BRAF mutated primary tumors in the dataset, while rearrangement of BRAF with a variety of genes seemed to occur in only 4.36% of these samples. In the majority of cases where a V600 variant exists, the valine residue is substituted by glutamic acid (V600E), enhancing the serine/threonine kinase activity of BRAF, thus leading to the abrogation of extracellular signals, promoting cell growth and proliferation [66][67][68].
In contrast to BRAF, there is no hotspot position for the NF1 gene. The most common somatic mutation of NF1, namely R2450*, barely exceeds 3% of all identified variants in the cohort. In addition, the analysis showed that nonsense mutations, frameshift deletions and splice-site variants are the most frequent mutation types for this gene in cancer, accounting for 39.91%, 20.83% and 15.79% of all identified variants, respectively. Regardless of the mutation type, in the majority of NF1-affected cases, mutations lead to a loss of neurofibromin GTPase-activating function, resulting in sustainably high GTP-bound levels of RAS proteins and thereby in a continuous tumor-promoting signaling process via RTK-RAS and PI3K/AKT pathway hyperactivation [69][70][71][72].

4. Lipid Metabolism

Both lipid synthesis and catabolism are essential for the maintenance of membrane functionality, protein trafficking, immune cell responses, signaling, as well as coverage of metabolic demands, such as energy production and storage [73][74][75][76][77]. It has been shown that cancer cells manage to retain a high proliferative potential, through various metabolic modifications [7][78][79]. According to the analysis, more than 40% of patients of one in three cancer types/subtypes are characterized by driver mutations in genes involved in lipid metabolism. In uterine endometrioid carcinoma, astrocytoma, oligodendroglioma and oligoastrocytoma this proportion reached or exceeded 80%, while, as with the two pathways discussed above, no primary uveal melanoma tumor of the dataset was affected. At the gene level, PIK3CA, PTEN and IDH1 occupy the first places in the mutagenicity ranking, as they were found altered in 45.21%, 27.56% and 16.93% of the patients, respectively. Over 95% of PIK3CA somatic alterations in cancer are missense mutations, half of which include three substitutions: E545K, H1047R and E542K. These substitutions exert a gain-of-function effect on the PI3K protein via two different mechanisms. Amino acid (aa) residues E545 and E542 are located in the helical domain of p110alpha protein and their substitution by a lysine residue attenuates the inhibitory interaction between the catalytic subunit (p110alpha) and the nSH2 domain of the regulatory subunit (p85alpha) of the PI3K protein, promoting the continuous activation of PI3K [80][81]. A constitutive PI3K activation is also the result of the kinase domain variant H1047R, but in this case, p110alpha abolishes its C-terminal tail self-inhibitory capacity [82]. Both mechanisms lead to a strong activation of PI3K downstream effectors, such as the AKT and P70S6K proteins, which mediate protein synthesis, cell growth, cell proliferation, angiogenesis, survival, and thus contribute to tumorigenic transformation [83][84][85][86]. At the same time, hyper-activated PI3K/AKT signaling induces the expression of genes involved in fatty acid anabolism, a process that generates the essential building blocks for the synthesis of new cells [87][88].
PTEN alterations show greater variety than PIK3CA alterations, with missense mutations, frameshift insertion-deletions (indels) and nonsense mutations representing 91% of all carriers. The most prevalent mutations involve R130, R233 and T319 aa residues and are found in 17.5%, 5% and 4.74% of all affected patients, respectively. In the majority of cases, arginine in position 130 is either substituted by a glutamine or a glycine residue, or, as in the cases of R233 and T319, the codon that is responsible for encoding it, is converted to a stop codon. Whereas truncating mutations such as R130*, R233* and T319* lead to an unstable, non-functional protein product [89][90][91], R130Q and R130G variants generate stable proteins, which, however, lack phosphatase activity [90][92]. Absence or non-functionality of the PTEN protein prevents PIP3 dephosphorylation, which in turn accumulates and recruits PI3K signaling effectors, such as AKT and PDK1 [93]. Furthermore, it was recently shown that PTENR130Q mutants tend to accumulate at the cell periphery where they form leading edges that increase tumor invasiveness and further activate the PI3K/AKT signaling axis [94].
A very impressive paradigm of a predominant mutational hotspot is represented by the IDH1 gene. Of the 467 somatic driver mutations that was identified in an equal number of cancer patients, 466 carried an R132 replacement, with histidine being the most frequent substitute (388/466 cases); cysteine, glycine, serine and leucine substitutions occurred in 50, 16, 11 and one patients, respectively. These variants, which are mapped in the catalytic pocket of the enzyme, make isocitrate dehydrogenase-1 convert the normal final product of its catalytic activity, alpha-ketoglutarate (aKG), into R(−)-2-hydroxyglutarate (2HG), with concomitant NADPH consumption [95][96]. The following 2HG-mediated inhibition of aKG-dependent deoxygenases, such as TET2 and JMJD2A/C, promotes global gene expression changes, which along with the redox stress arising from the declined NADPH levels, reflect the tumorigenic impact of these mutations [96][97][98][99]. Likewise, even though the decreased levels of two lipogenesis components, NADPH and aKG [100] would be expected to abrogate lipid synthesis, certain lipid precursors, such as glycerol-phosphates and glycerophosphocholine, are present in elevated quantities; on the other hand, other lipid precursors, as for example myo-inositol phosphate, are present in reduced levels, compared to unaffected tumors, suggesting that cancer cells harboring IDH1 variants, alter their phospholipid expression profile, probably in a tumor-assisting manner [101][102][103].
As made clear from the above, signaling changes involving lipid metabolism regulators perturb a wide spectrum of cellular processes and contribute to cancer development. This observation has led to the development of therapies that mitigate these changes. Currently, there are eleven clinically available therapies that target the signaling of four out of the 24 lipid metabolism-related genes found mutated in the dataset [104]. As the analysis suggests, when lipid metabolism is deregulated on account of a genetic change, this alteration invariably affects one of its aforementioned PI3K/AKT signaling-mediating regulators. Hence, inhibition of the PI3K/AKT signaling axis is suggested to be the main goal of personalized medicine for the treatment of tumors bearing such alterations. When PI3K catalytic subunit inhibitors, both isoform-specific, such as alpelisib, and pan-isoform, such as copanlisib and duvelisib, as well as selective MTOR inhibitors, including everolimus and temsirolimus, are employed, they seem to offer a significant PFS—or even OS—benefit to patients with a variety of blood or solid malignancies [105][106][107][108][109]. In addition, ivosidenib, an inhibitor of IDH1R132 mutants, has been approved by the FDA, for the treatment of acute myeloid leukemia (AML) patients harboring these variants [110], while its effectiveness in other IDH1-deficient cancer types is currently being tested in several ongoing clinical trials (e.g., advanced and metastatic cholangiocarcinoma/NCT02989857, chondrosarcoma/NCT04278781, cholangiocarcinoma—chondrosarcoma—glioma—other advanced solid tumors/NCT02073994, recurrent ependymoma—recurrent ewing sarcoma—recurrent hepatoblastoma/NCT04195555, etc.).

5. The PI3K/AKT Pathway

The impact of the PI3K/AKT signaling network on diverse cellular functions is well established. Many of these, including cell growth and proliferation, survival, motility, cellular metabolism, immune system functions and angiogenesis, are tightly intertwined with cancer development and progression and as a result a lot of  has been dedicated to unraveling the deregulation mechanisms of this pathway in cancer [111][112][113][114]. In 26 of the 36 cancer types of the dataset, more than 10% of patients carried at least one driver mutation in genes involved in this pathway. Uterine malignancies showed the highest mutational rates with 93.3% of uterine endometrioid carcinoma patients being affected, while the corresponding proportion of the remaining uterine tumors analyzed exceeded 60%. On the other hand, less than 5% of serous ovarian cancer, papillary thyroid cancer, pheochromocytoma, uveal melanoma and acute myeloid leukemia patients appeared to bear such changes (Figure 1). Among all PI3K/AKT-deregulated tumors examined, 53.75% harbored driver mutations in PIK3CA, 32.76% in PTEN and 12.93% in PIK3R1, with the rest of the genes in this pathway being altered in less than 6% of the tumors each. Interestingly, simultaneous mutations in at least two, or in certain situations in all of the above mentioned top mutated genes, were present in 16.34% of these patients. As driver mutations and therapeutic applications regarding PIK3CA and PTEN genes were discussed earlier in this report, it will more focused on the PIK3R1 gene. Somatic mutations in PIK3R1 exhibit a highly scattered pattern. The absence of predominant hotspots is reflected by the mutational rates of the most prevalent genetic changes of this gene; 6.67% for R348*, 5.67% for X582_splice and 4% for G376R. R348* is a truncating but gain-of-function mutation that exerts its tumorigenic impact in both a PI3K/AKT-dependent and a PI3K/AKT-independent manner. In addition to activating PI3K/AKT signaling, p85alpha mutants are localized into the nucleus and promote the activation of ERK and JNK kinases, thereby inhibiting FASL-mediated apoptosis and inducing cell survival, growth, proliferation and invasion [115][116]. Even though X582 splice alteration has been previously identified and considered as pathogenic [117], its exact functional consequences have not been elucidated yet. Finally, the nSH2 domain-located G376R substitution acts in the same way as the previously discussed E545 and E542 substitutions of the p110alpha protein, thus attenuating the inhibitory interaction between the regulatory and the catalytic subunit of the PI3K complex and enhancing the PI3K/AKT signaling [118][119].
Overall, the PI3K/AKT signaling-promoting behavior of p85alpha mutants, places PIK3R1-targeting in the same therapeutic context as the other major effectors of this pathway, PIK3CA and PTEN.

6. Ubiquitination and Acetylation Pathways

Ubiquitination is a reversible modification that leads either to protein degradation or to the regulation of protein–protein interactions. It is essential for the appropriate execution of various cellular events, namely inflammation, translation, endocytosis, DNA damage response (DDR), protein trafficking, differentiation and signal transduction [120][121][122][123][124]. Thus, deregulation of the ubiquitin pathway can lead to cancer initiation and/or progression. Mutations in genes encoding components or regulators of the ubiquitination machinery are not uncommon in cancer samples. The analysis demonstrates that such mutations are present in more than 10% of patients, in two out of three cancer types (24/36). The highest rates are shown in uterine carcinosarcoma, mucinous adenocarcinoma of the colon and rectum, uterine endometrioid carcinoma and breast invasive lobular carcinoma, ranging from ~42% to ~57%. Contrariwise, oligodendroglioma, papillary thyroid cancer, leiomyosarcoma, uveal melanoma and pheochromocytoma, exhibited the lowest rates with less than 3% of the patients being affected (Figure 3). At the gene level, the most frequently mutated genes, FBXW7 (or FBW7), EP300 and CREBBP (or CBP) were detected in 19.6%, 10.72% and 9.88%, respectively, of ubiquitination/deubiquitination-deficient tumors, while the mutational rate of nine more genes ranged between ~5% and ~9%. In descending order of mutational frequency, these are as follows: KMT2B, RNF43, VHL, MAP3K1, KMT2A, SPOP, BAP1, KEAP1 and BRCA1.
Three arginine residues of the FBW7 ubiquitin ligase—R465, R505 and R479—represent 43.59% of all FBW7 somatic driver mutations in primary tumor samples. These positions are located into the WD40 domain, which constitutes the substrate-binding site of the SCF complex (a type of E3 ligase), which is responsible for the ubiquitin-labeling and the subsequent proteasome-mediated degradation of its protein effectors [125][126]. These mutations induce changes in the WD40 domain, altering the interaction potential of FBW7, probably via both hydrophobic and electrostatic interactions, as well as by limiting the contact surface because of the shorter substitute sidechains (mainly cysteine, histidine, glycine and glutamine) [127]. Given that several FBW7 interactors act as regulators of cell growth, apoptosis and proliferation [128][129][130][131][132][133]; prevention of their degradation may result in tumorigenesis.
Even though the EP300 gene is usually altered by nonsense mutations, the most recurrent mutations fall into three other categories. The D1399N substitution is the most prevalent somatic mutation of this gene, accounting for 7.29% of EP300-mutated primary tumors in the working dataset. Missense mutations in this position were shown to change the conformation of the p300 protein histone acetyltransferase (HAT) domain, leading to abolishment of its autoacetylation activity, which is essential for appropriate function [134][135]. The subsequent inability of p300 to stimulate other tumor suppressors in the nucleus, such as RB1, BRCA1, p53 and AP-2alpha [136][137][138][139][140], paves the way for the predominance of its spatial distinct, cytoplasmic ubiquitin ligase activity, which targets p53 for degradation [141][142][143]. These changes, together with the reduced global levels of histone H3 acetylation [144], contribute to the tumorigenic impact of this genetic alteration. The second and third most prevalent mutations of the EP300 gene are the frameshift deletion M1470Cfs*26 and the splice site variant X1429 splice, and were each identified in 2.6% of EP300-affected patients. However, their functional impact is not clear. Another gene with intrinsic histone acetyltransferase activity, sharing high similarity to EP300, is the CREBBP gene. Missense mutations involving the R1446 are the most recurrent somatic mutations of CREBBP, followed by frameshift indels involving I1084 and substitutions of D1435, accounting for 7.91%, 5.65% and 2.82% of CREBBP-affected primary tumors, respectively. Both R1446 and D1435 are located in the HAT domain, which is responsible for the catalytic activity of the CBP transcriptional coactivator. Substitution of these aa residues, reduces the acetyl-CoA binding affinity of CBP, thereby impairing its acetyltransferase activity [145][146][147]. Consequently, CBP can neither activate p53 tumor suppressor nor inactivate BCL6 proto-oncoprotein. Furthermore, as with its structurally and functionally related p300 protein, CBP also exhibits an E4 ubiquitin ligase activity targeting p53 for degradation in the cytoplasm [141]. These observations, in conjunction with the arisen extended transcriptional changes, dictate a tumor promoting effect for these mutations [145][148]. The functional impact of frameshift deletion I1084Sfs*15, which is found in 4.52% of CREBBP-altered samples thus far remains obscure.
Proteins involved in either the attachment or the removal of ubiquitin moieties are barely exploited in clinical practice nowadays [149]. An exception to this rule is provided by thalidomide analogues lenalidomide and pomalidomide, which have been approved for the treatment of various blood malignancies and exhibit anti-tumor activities by altering the specificity of cereblon, which constitutes the substrate recognition component of the CRL4 E3 ubiquitin ligase complex [150][151]. Nonetheless, targeting of the proteolytic machinery is primarily oriented to proteasome inhibition, with three inhibitors—bortezomib, carfilzomib and ixazomib—already approved for the treatment of multiple myeloma and mantle cell lymphoma [152], while other agents, such as delanzomib (CEP-18770) and marizomib or salinosporamide A (NPI-0052) [153] are currently being tested in clinical trials as potential treatment options for solid tumors (NCT00572637 and NCT03345095, respectively).

7. The WNT/b Catenin Pathway

The WNT/b catenin pathway is one of the best-studied signaling cascades in cancer development, known to be implicated in several cancer-related cellular functions, such as cell proliferation, stem cell maintenance, differentiation, cell–cell adhesion, morphogenetic processes, migration, angiogenesis and immune evasion [154][155][156][157][158]. Mutations in WNT/b catenin components are very common in cancer patients. The analysis revealed that carcinogenic mutational occurrences in genes of this pathway are limited compared to the pathways discussed so far. Specifically, the proportion of patients with at least one driver mutation in this pathway exceeded 10% in only nine of the thirty-six cancer types examined here. Intestinal malignancies ranked highest in terms of mutational landscape with at least 80% of colon adenocarcinoma, rectal adenocarcinoma and mucinous adenocarcinoma of the colon and rectum patients harboring driver alterations. On the other hand, no such mutations were found in uveal melanoma or leiomyosarcoma patients (Figure 1). Among WNT/b catenin effectors, the APC, CTNNB1 and RNF43 genes were found mutated in 48.59%, 26.41% and 14.94% of the affected samples, respectively, while four other genes (in descending order of mutational frequency: AMER1, AXIN1, TCF7L2 and AXIN2) exhibited a driver mutational rate between ~5% and ~8%.
The most frequent mutations are nonsense mutations in the APC tumor suppressor, present in 40.6% of patients. Conversion of arginine-encoding codons into stop codons predominantly takes place at positions 1450, 876 and 1114 of the APC protein (8.51%, 4.84% and 4.64% respectively). R1450 is located into the so-called mutation cluster region (MCR) [159]. Truncation of the APC protein in this position leads to loss of all axin- and most b catenin-binding sites, therefore abrogating the ability of APC to negatively regulate b catenin via the formation of the destruction complex AXIN-APC-CK1alpha-GSK3beta [160][161][162][163]. Similarly, two other truncations, namely the R1114* and R876* mutants, also lose the axin- and most b catenin-binding sites [164][165]. In all three cases, the subsequent b catenin accumulation and nuclear entry permits activation of the TCF/LEF1 transcriptional complex, thereby promoting cellular proliferation and tumorigenesis [162].
Somatic mutations in the CTNNB1 (catenin-beta 1) gene, which is involved in the regulation of cell adhesion and gene transcription, are almost exclusively missense mutations. In particular, aa substitutions at six specific positions (32, 33, 34, 37, 41 and 45) represent more than 85% of all affected patients in the dataset. Among them, S33, S37 and D32 replacements were the most prevalent, affecting 18.51%, 17.44% and 16.01% of all cases, respectively. The protein region between D32 and S45 participates in the phosphorylation of b catenin from CK1alpha and GSK3beta (components of its destruction complex), as well as in the interaction of phosphorylated b catenin with its E3 ligase substrate recognition component, FBW1 [166][167]. Consequently, mutations in these protein sites exert similar signaling implications to the ones exerted by APC, as b catenin escapes proteasomal degradation and confers an increased proliferative potential to the cell [167][168][169][170][171].
Another gene found mutated in cancer patients is the RNF43 (Ring Finger Protein 43), a downstream target gene of Wnt/b catenin signaling. Almost seventy-three percent of RNF43-mutated primary tumors carry a frameshift deletion in this gene, while the second most frequent alteration type is a non-sense mutation (~17%). By far the most common alteration of the RNF43 protein is G659Vfs*41, being present in approximately 60% of all RNF43-mutated tumors. Interestingly, despite its recurrent presence in cancer samples, this frameshift deletion leaves protein function intact, with the relevant RNF43-mutant being able to exert its E3 ubiquitin ligase activity [172]; this results in the tagging of FZD family (frizzled transmembrane proteins) WNT receptors for proteasomal degradation and in the inactivation of WNT/b catenin signaling [173][174]. The second and third most frequent somatic mutations of the RNF43 protein are R519* and R145*, affecting only 2.52% and 1.89% of all carriers, respectively. Both of these aberrations lead to a truncated protein with a WNT signaling-enhancing role, however the exact mechanism differs depending on the truncation position. The catalytic RING domain of RNF43 lies among P270 and I316 [172][175], and as such the R519* mutant retains its E3 ubiquitin ligase activity. Nonetheless, it simultaneously gains the ability to snare CK1alpha at the plasma membrane, thus assisting b catenin to escape degradation [176]. On the other hand, R145* variants lack this catalytic activity and are therefore expected to abort their FZD degradation and b catenin destabilization role [172].
Significant efforts have been made to therapeutically target the WNT/b catenin network, mostly for the development of small molecule stabilizers of the b catenin destruction complex components or destabilizers of the b catenin-TCF/LEF interaction, but also for the development of antibodies and regulatory peptides that directly or indirectly affect—mostly inhibit—WNT or FZD proteins [162][177][178]. Four such constructs have exhibited the most encouraging results and their efficacy is currently evaluated in phase II clinical trials of both solid and blood cancer patients. In this context, WNT974 (NCT02278133)—a porcupine inhibitor that impedes WNT secretion and activity, Foxy-5 (NCT03883802)—a WNT5a mimetic, PRI-724 (NCT01606579)—an antagonist of the b catenin coactivator CBP, and DKN-01 (NCT03395080)—a monoclonal antibody that neutralizes the activity of WNT/b catenin axis inhibitor DKK1, are now in the spotlight of WNT pathway targeting.

8. The Notch Pathway

Notch is a cancer-related signaling pathway well-known for its involvement in a variety of developmental processes, as well as cellular differentiation, proliferation, stem cell maintenance, angiogenesis, EMT, inflammation and apoptosis [179][180][181]. Mutations in the Notch pathway, were found in at least one in ten patients in fifteen out of thirty-six assessed cancer types. Uterine carcinosarcoma exhibited the highest driver mutational rate (40.35%), followed by mucinous adenocarcinoma of the colon and rectum (33.93%) and bladder urothelial carcinoma (29.02%), while other gynecological and upper digestive tract malignancies, were also highly affected. On the other hand, none of the patients with pheochromocytoma and no more than 2% of patients with leiomyosarcoma, uveal melanoma and papillary thyroid cancer carried such mutations (Figure 1). At the gene level, the most frequently mutated components or regulators of the Notch pathway appeared to be identical to the above discussed ubiquitination pathways; FBXW7, EP300 and CREBBP were found altered in 33.65%, 18.41% and 16.97% of Notch-impaired tumors, respectively, while somatic driver events in each of the SPEN, NCOR1 and NOTCH1 genes, were detected in ~12% of cases. Upon activation of the NOTCH receptors by their ligands (e.g., delta-like protein 1, protein jagged-1 etc), the NOTCH-intracellular domain (NICD) is released and transferred into the nucleus where it acts as a transcription regulator. NICD is one of the FBW7 substrates [129] and mutations within the FBW7 WD40 domain have been reported to impede this interplay, therefore leading to NICD accumulation and enhanced Notch signaling, which may lead to a tumorigenic outcome [127][182][183]. Furthermore, despite the previously reported p300 requirement for NICD transcriptional activity [184][185], it was recently demonstrated that loss-of-function mutations in either the EP300 or CREBBP gene can also activate the Notch axis, due to the subsequent low histone acetylation levels of the FBXW7 promoter [186], suggesting the implication of additional transcriptional NICD co-activators.
So far, no targeted therapies for Notch signaling regulation have entered the clinical practice. However, remarkable efforts have been made to overcome the obstacles associated with Notch pathway signaling, given the highly context-specific behavior of this signaling axis in cancer [187]. To this end, diverse strategies have been utilized, such as the targeting of NOTCH biosynthesis enzymes, receptor-ligand interplay, NOTCH cleavage-performing effectors or NICD-containing transcriptional complexes assemblage [187][188][189]. The most encouraging results come from the development of inhibitors against gamma-secretase—which is responsible for the final NICD-releasing NOTCH cleavage—and delta-like protein 3, a NOTCH ligand, with some of the relevant cancer-related clinical trials being in advanced stages. Specifically, the efficacy of gamma-secretase inhibitors (GSIs) nirogacestat/PF-03084014 (NCT03785964) and MK0752 (NCT00756717) is currently evaluated in phase III trials in adults with desmoid tumor and in early stage breast cancer patients in combination with tamoxifen respectively, while the tesirine conjugated anti-delta-like protein 3 mAb rovalpituzumab (Rova-T) (NCT03061812) is being tested in a phase III clinical trial in small-cell lung cancer (SCLC) patients with disease progression following platinum-based chemotherapy and overexpressing delta-like protein 3.

This entry is adapted from the peer-reviewed paper 10.3390/cancers14030664

References

  1. Parui, A.L.; Bose, K. Cancer Biology and Its Treatment Modalities: A Brief Historical Perspective. In Unravelling Cancer Signaling Pathways: A Multidisciplinary Approach; Bose, K., Chaudhari, P., Eds.; Springer: Singapore, 2019; pp. 1–11.
  2. Martincorena, I.; Campbell, P.J. Somatic mutation in cancer and normal cells. Science 2016, 349, 1483–1489, Erratum in Science 2016, 351, aaf5401.
  3. Okugawa, Y.; Grady, W.M.; Goel, A. Epigenetic Alterations in Colorectal Cancer: Emerging Biomarkers. Gastroenterology 2015, 149, 1204–1225.e1212.
  4. Sever, R.; Brugge, J.S. Signal transduction in cancer. Cold Spring Harb. Perspect. Med. 2015, 5, a006098.
  5. Baylin, S.B.; Jones, P.A. Epigenetic Determinants of Cancer. Cold Spring Harb. Perspect. Biol. 2016, 8.
  6. Feinberg, A.P.; Koldobskiy, M.A.; Gondor, A. Epigenetic modulators, modifiers and mediators in cancer aetiology and progression. Nat. Rev. Genet. 2016, 17, 284–299.
  7. Hanahan, D.; Weinberg, R.A. Hallmarks of cancer: The next generation. Cell 2011, 144, 646–674.
  8. Sanchez-Vega, F.; Mina, M.; Armenia, J.; Chatila, W.K.; Luna, A.; La, K.C.; Dimitriadoy, S.; Liu, D.L.; Kantheti, H.S.; Saghafinia, S.; et al. Oncogenic Signaling Pathways in The Cancer Genome Atlas. Cell 2018, 173, 321–337.e310.
  9. Vogelstein, B.; Kinzler, K.W. Cancer genes and the pathways they control. Nat. Med. 2004, 10, 789–799.
  10. Dempke, W.C.M.; Fenchel, K.; Uciechowski, P.; Chevassut, T. Targeting Developmental Pathways: The Achilles Heel of Cancer? Oncology 2017, 93, 213–223.
  11. Pon, J.R.; Marra, M.A. Driver and passenger mutations in cancer. Annu. Rev. Pathol. 2015, 10, 25–50.
  12. Vogelstein, B.; Lane, D.; Levine, A.J. Surfing the p53 network. Nature 2000, 408, 307–310.
  13. Oren, M. Decision making by p53: Life, death and cancer. Cell Death Differ. 2003, 10, 431–442.
  14. Harris, S.L.; Levine, A.J. The p53 pathway: Positive and negative feedback loops. Oncogene 2005, 24, 2899–2908.
  15. Jones, R.G.; Plas, D.R.; Kubek, S.; Buzzai, M.; Mu, J.; Xu, Y.; Birnbaum, M.J.; Thompson, C.B. AMP-activated protein kinase induces a p53-dependent metabolic checkpoint. Mol. Cell 2005, 18, 283–293.
  16. Labuschagne, C.F.; Zani, F.; Vousden, K.H. Control of metabolism by p53–Cancer and beyond. Biochim. Biophys. Acta Rev. Cancer 2018, 1870, 32–42.
  17. Levine, A.J.; Oren, M. The first 30 years of p53: Growing ever more complex. Nat. Rev. Cancer 2009, 9, 749–758.
  18. Aubrey, B.J.; Strasser, A.; Kelly, G.L. Tumor-Suppressor Functions of the TP53 Pathway. Cold Spring Harb. Perspect. Med. 2016, 6, a026062.
  19. Haronikova, L.; Olivares-Illana, V.; Wang, L.; Karakostis, K.; Chen, S.; Fahraeus, R. The p53 mRNA: An integral part of the cellular stress response. Nucleic Acids Res. 2019, 47, 3257–3271.
  20. Muller, P.A.; Vousden, K.H. p53 mutations in cancer. Nat. Cell Biol. 2013, 15, 2–8.
  21. Li, J.; Yang, L.; Gaur, S.; Zhang, K.; Wu, X.; Yuan, Y.C.; Li, H.; Hu, S.; Weng, Y.; Yen, Y. Mutants TP53 p.R273H and p.R273C but not p.R273G enhance cancer cell malignancy. Hum. Mutat. 2014, 35, 575–584.
  22. Sun, S.; Chen, H.; Sun, L.; Wang, M.; Wu, X.; Xiao, Z.J. Hotspot mutant p53-R273H inhibits KLF6 expression to promote cell migration and tumor metastasis. Cell Death Dis. 2020, 11, 595.
  23. Schulz-Heddergott, R.; Stark, N.; Edmunds, S.J.; Li, J.; Conradi, L.C.; Bohnenberger, H.; Ceteci, F.; Greten, F.R.; Dobbelstein, M.; Moll, U.M. Therapeutic Ablation of Gain-of-Function Mutant p53 in Colorectal Cancer Inhibits Stat3-Mediated Tumor Growth and Invasion. Cancer Cell 2018, 34, 298–314.e297.
  24. Klemke, L.; Fehlau, C.F.; Winkler, N.; Toboll, F.; Singh, S.K.; Moll, U.M.; Schulz-Heddergott, R. The Gain-of-Function p53 R248W Mutant Promotes Migration by STAT3 Deregulation in Human Pancreatic Cancer Cells. Front. Oncol. 2021, 11, 642603.
  25. Yu, X.; Vazquez, A.; Levine, A.J.; Carpizo, D.R. Allele-specific p53 mutant reactivation. Cancer Cell 2012, 21, 614–625.
  26. Grugan, K.D.; Vega, M.E.; Wong, G.S.; Diehl, J.A.; Bass, A.J.; Wong, K.K.; Nakagawa, H.; Rustgi, A.K. A common p53 mutation (R175H) activates c-Met receptor tyrosine kinase to enhance tumor cell invasion. Cancer Biol. Ther. 2013, 14, 853–859.
  27. Parry, D.; Peters, G. Temperature-sensitive mutants of p16CDKN2 associated with familial melanoma. Mol. Cell Biol. 1996, 16, 3844–3852.
  28. Rutter, J.L.; Goldstein, A.M.; Davila, M.R.; Tucker, M.A.; Struewing, J.P. CDKN2A point mutations D153spl(c.457G>T) and IVS2+1G>T result in aberrant splice products affecting both p16INK4a and p14ARF. Oncogene 2003, 22, 4444–4448.
  29. Kannengiesser, C.; Brookes, S.; del Arroyo, A.G.; Pham, D.; Bombled, J.; Barrois, M.; Mauffret, O.; Avril, M.F.; Chompret, A.; Lenoir, G.M.; et al. Functional, structural, and genetic evaluation of 20 CDKN2A germ line mutations identified in melanoma-prone families or patients. Hum. Mutat. 2009, 30, 564–574.
  30. Angele, S.; Jones, C.; Reis Filho, J.S.; Fulford, L.G.; Treilleux, I.; Lakhani, S.R.; Hall, J. Expression of ATM, p53, and the MRE11-Rad50-NBS1 complex in myoepithelial cells from benign and malignant proliferations of the breast. J. Clin. Pathol. 2004, 57, 1179–1184.
  31. Bailey, S.L.; Gurley, K.E.; Hoon-Kim, K.; Kelly-Spratt, K.S.; Kemp, C.J. Tumor suppression by p53 in the absence of Atm. Mol. Cancer Res. 2008, 6, 1185–1192.
  32. Biddlestone-Thorpe, L.; Sajjad, M.; Rosenberg, E.; Beckta, J.M.; Valerie, N.C.; Tokarz, M.; Adams, B.R.; Wagner, A.F.; Khalil, A.; Gilfor, D.; et al. ATM kinase inhibition preferentially sensitizes p53-mutant glioma to ionizing radiation. Clin. Cancer Res. 2013, 19, 3189–3200.
  33. Malbert-Colas, L.; Ponnuswamy, A.; Olivares-Illana, V.; Tournillon, A.S.; Naski, N.; Fahraeus, R. HDMX folds the nascent p53 mRNA following activation by the ATM kinase. Mol. Cell 2014, 54, 500–511.
  34. Chwastek, J.; Jantas, D.; Lason, W. The ATM kinase inhibitor KU-55933 provides neuroprotection against hydrogen peroxide-induced cell damage via a gammaH2AX/p-p53/caspase-3-independent mechanism: Inhibition of calpain and cathepsin D. Int. J. Biochem. Cell Biol. 2017, 87, 38–53.
  35. Karakostis, K.; Vadivel Gnanasundram, S.; Lopez, I.; Thermou, A.; Wang, L.; Nylander, K.; Olivares-Illana, V.; Fahraeus, R. A single synonymous mutation determines the phosphorylation and stability of the nascent protein. J. Mol. Cell Biol. 2019, 11, 187–199.
  36. Hwang, S.Y.; Kuk, M.U.; Kim, J.W.; Lee, Y.H.; Lee, Y.S.; Choy, H.E.; Park, S.C.; Park, J.T. ATM mediated-p53 signaling pathway forms a novel axis for senescence control. Mitochondrion 2020, 55, 54–63.
  37. Easton, D.F.; Pharoah, P.D.; Antoniou, A.C.; Tischkowitz, M.; Tavtigian, S.V.; Nathanson, K.L.; Devilee, P.; Meindl, A.; Couch, F.J.; Southey, M.; et al. Gene-panel sequencing and the prediction of breast-cancer risk. N. Engl. J. Med. 2015, 372, 2243–2257.
  38. Griffith, O.L.; Spies, N.C.; Anurag, M.; Griffith, M.; Luo, J.; Tu, D.; Yeo, B.; Kunisaki, J.; Miller, C.A.; Krysiak, K.; et al. The prognostic effects of somatic mutations in ER-positive breast cancer. Nat. Commun. 2018, 9, 3476.
  39. Nahar, R.; Zhai, W.; Zhang, T.; Takano, A.; Khng, A.J.; Lee, Y.Y.; Liu, X.; Lim, C.H.; Koh, T.P.T.; Aung, Z.W.; et al. Elucidating the genomic architecture of Asian EGFR-mutant lung adenocarcinoma through multi-region exome sequencing. Nat. Commun. 2018, 9, 216.
  40. Jette, N.R.; Kumar, M.; Radhamani, S.; Arthur, G.; Goutam, S.; Yip, S.; Kolinsky, M.; Williams, G.J.; Bose, P.; Lees-Miller, S.P. ATM-Deficient Cancers Provide New Opportunities for Precision Oncology. Cancers 2020, 12, 687.
  41. Zhu, G.; Pan, C.; Bei, J.X.; Li, B.; Liang, C.; Xu, Y.; Fu, X. Mutant p53 in Cancer Progression and Targeted Therapies. Front. Oncol. 2020, 10, 595187.
  42. Salomao, N.; Karakostis, K.; Hupp, T.; Vollrath, F.; Vojtesek, B.; Fahraeus, R. What do we need to know and understand about p53 to improve its clinical value? J. Pathol. 2021, 254, 443–453.
  43. Duffy, M.J.; Synnott, N.C.; O’Grady, S.; Crown, J. Targeting p53 for the treatment of cancer. Semin. Cancer Biol. 2020.
  44. Dhillon, S. Palbociclib: First global approval. Drugs 2015, 75, 543–551.
  45. Kim, E.S. Abemaciclib: First Global Approval. Drugs 2017, 77, 2063–2070.
  46. Syed, Y.Y. Ribociclib: First Global Approval. Drugs 2017, 77, 799–807.
  47. Dhillon, S. Trilaciclib: First Approval. Drugs 2021, 81, 867–874.
  48. Young, R.J.; Waldeck, K.; Martin, C.; Foo, J.H.; Cameron, D.P.; Kirby, L.; Do, H.; Mitchell, C.; Cullinane, C.; Liu, W.; et al. Loss of CDKN2A expression is a frequent event in primary invasive melanoma and correlates with sensitivity to the CDK4/6 inhibitor PD0332991 in melanoma cell lines. Pigment Cell Melanoma Res. 2014, 27, 590–600.
  49. Su, D.; Zhang, D.; Jin, J.; Ying, L.; Han, M.; Chen, K.; Li, B.; Wu, J.; Xie, Z.; Zhang, F.; et al. Identification of predictors of drug sensitivity using patient-derived models of esophageal squamous cell carcinoma. Nat. Commun. 2019, 10, 5076.
  50. DeMichele, A.; Clark, A.S.; Tan, K.S.; Heitjan, D.F.; Gramlich, K.; Gallagher, M.; Lal, P.; Feldman, M.; Zhang, P.; Colameco, C.; et al. CDK 4/6 inhibitor palbociclib (PD0332991) in Rb+ advanced breast cancer: Phase II activity, safety, and predictive biomarker assessment. Clin. Cancer Res. 2015, 21, 995–1001.
  51. Finn, R.S.; Crown, J.P.; Lang, I.; Boer, K.; Bondarenko, I.M.; Kulyk, S.O.; Ettl, J.; Patel, R.; Pinter, T.; Schmidt, M.; et al. The cyclin-dependent kinase 4/6 inhibitor palbociclib in combination with letrozole versus letrozole alone as first-line treatment of oestrogen receptor-positive, HER2-negative, advanced breast cancer (PALOMA-1/TRIO-18): A randomised phase 2 study. Lancet Oncol. 2015, 16, 25–35.
  52. Arnedos, M.; Bayar, M.A.; Cheaib, B.; Scott, V.; Bouakka, I.; Valent, A.; Adam, J.; Leroux-Kozal, V.; Marty, V.; Rapinat, A.; et al. Modulation of Rb phosphorylation and antiproliferative response to palbociclib: The preoperative-palbociclib (POP) randomized clinical trial. Ann. Oncol. 2018, 29, 1755–1762.
  53. Rose, T.L.; Chism, D.D.; Alva, A.S.; Deal, A.M.; Maygarden, S.J.; Whang, Y.E.; Kardos, J.; Drier, A.; Basch, E.; Godley, P.A.; et al. Phase II trial of palbociclib in patients with metastatic urothelial cancer after failure of first-line chemotherapy. Br. J. Cancer 2018, 119, 801–807.
  54. Toulmonde, M.; Blay, J.Y.; Bouche, O.; Mir, O.; Penel, N.; Isambert, N.; Duffaud, F.; Bompas, E.; Esnaud, T.; Boidot, R.; et al. Activity and Safety of Palbociclib in Patients with Advanced Gastrointestinal Stromal Tumors Refractory to Imatinib and Sunitinib: A Biomarker-driven Phase II Study. Clin. Cancer Res. 2019, 25, 4611–4615.
  55. Mateo, J.; Carreira, S.; Sandhu, S.; Miranda, S.; Mossop, H.; Perez-Lopez, R.; Nava Rodrigues, D.; Robinson, D.; Omlin, A.; Tunariu, N.; et al. DNA-Repair Defects and Olaparib in Metastatic Prostate Cancer. N. Engl. J. Med. 2015, 373, 1697–1708.
  56. Schmitt, A.; Knittel, G.; Welcker, D.; Yang, T.P.; George, J.; Nowak, M.; Leeser, U.; Buttner, R.; Perner, S.; Peifer, M.; et al. ATM Deficiency Is Associated with Sensitivity to PARP1- and ATR Inhibitors in Lung Adenocarcinoma. Cancer Res. 2017, 77, 3040–3056.
  57. Lloyd, R.L.; Wijnhoven, P.W.G.; Ramos-Montoya, A.; Wilson, Z.; Illuzzi, G.; Falenta, K.; Jones, G.N.; James, N.; Chabbert, C.D.; Stott, J.; et al. Combined PARP and ATR inhibition potentiates genome instability and cell death in ATM-deficient cancer cells. Oncogene 2020, 39, 4869–4883.
  58. Downward, J. Targeting RAS signalling pathways in cancer therapy. Nat. Rev. Cancer 2003, 3, 11–22.
  59. Castellano, E.; Molina-Arcas, M.; Krygowska, A.A.; East, P.; Warne, P.; Nicol, A.; Downward, J. RAS signalling through PI3-Kinase controls cell migration via modulation of Reelin expression. Nat. Commun. 2016, 7, 11245.
  60. Imperial, R.; Toor, O.M.; Hussain, A.; Subramanian, J.; Masood, A. Comprehensive pancancer genomic analysis reveals (RTK)-RAS-RAF-MEK as a key dysregulated pathway in cancer: Its clinical implications. Semin. Cancer Biol. 2019, 54, 14–28.
  61. Smith, M.J.; Neel, B.G.; Ikura, M. NMR-based functional profiling of RASopathies and oncogenic RAS mutations. Proc. Natl. Acad. Sci. USA 2013, 110, 4574–4579.
  62. Cook, J.H.; Melloni, G.E.M.; Gulhan, D.C.; Park, P.J.; Haigis, K.M. The origins and genetic interactions of KRAS mutations are allele- and tissue-specific. Nat. Commun. 2021, 12, 1808.
  63. Feig, L.A.; Cooper, G.M. Relationship among guanine nucleotide exchange, GTP hydrolysis, and transforming potential of mutated ras proteins. Mol. Cell Biol. 1988, 8, 2472–2478.
  64. Poulin, E.J.; Bera, A.K.; Lu, J.; Lin, Y.J.; Strasser, S.D.; Paulo, J.A.; Huang, T.Q.; Morales, C.; Yan, W.; Cook, J.; et al. Tissue-Specific Oncogenic Activity of KRAS(A146T). Cancer Discov. 2019, 9, 738–755.
  65. Waters, A.M.; Der, C.J. KRAS: The Critical Driver and Therapeutic Target for Pancreatic Cancer. Cold Spring Harb. Perspect. Med. 2018, 8, a031435.
  66. Davies, H.; Bignell, G.R.; Cox, C.; Stephens, P.; Edkins, S.; Clegg, S.; Teague, J.; Woffendin, H.; Garnett, M.J.; Bottomley, W.; et al. Mutations of the BRAF gene in human cancer. Nature 2002, 417, 949–954.
  67. Cantwell-Dorris, E.R.; O’Leary, J.J.; Sheils, O.M. BRAFV600E: Implications for carcinogenesis and molecular therapy. Mol. Cancer Ther. 2011, 10, 385–394.
  68. Falini, B.; Martelli, M.P.; Tiacci, E. BRAF V600E mutation in hairy cell leukemia: From bench to bedside. Blood 2016, 128, 1918–1927.
  69. Ding, L.; Getz, G.; Wheeler, D.A.; Mardis, E.R.; McLellan, M.D.; Cibulskis, K.; Sougnez, C.; Greulich, H.; Muzny, D.M.; Morgan, M.B.; et al. Somatic mutations affect key pathways in lung adenocarcinoma. Nature 2008, 455, 1069–1075.
  70. Upadhyaya, M.; Kluwe, L.; Spurlock, G.; Monem, B.; Majounie, E.; Mantripragada, K.; Ruggieri, M.; Chuzhanova, N.; Evans, D.G.; Ferner, R.; et al. Germline and somatic NF1 gene mutation spectrum in NF1-associated malignant peripheral nerve sheath tumors (MPNSTs). Hum. Mutat. 2008, 29, 74–82.
  71. Brems, H.; Beert, E.; de Ravel, T.; Legius, E. Mechanisms in the pathogenesis of malignant tumours in neurofibromatosis type 1. Lancet Oncol. 2009, 10, 508–515.
  72. Hodis, E.; Watson, I.R.; Kryukov, G.V.; Arold, S.T.; Imielinski, M.; Theurillat, J.P.; Nickerson, E.; Auclair, D.; Li, L.; Place, C.; et al. A landscape of driver mutations in melanoma. Cell 2012, 150, 251–263.
  73. Zhou, D.; Mattner, J.; Cantu, C., 3rd; Schrantz, N.; Yin, N.; Gao, Y.; Sagiv, Y.; Hudspeth, K.; Wu, Y.P.; Yamashita, T.; et al. Lysosomal glycosphingolipid recognition by NKT cells. Science 2004, 306, 1786–1789.
  74. Groux-Degroote, S.; van Dijk, S.M.; Wolthoorn, J.; Neumann, S.; Theos, A.C.; De Maziere, A.M.; Klumperman, J.; van Meer, G.; Sprong, H. Glycolipid-dependent sorting of melanosomal from lysosomal membrane proteins by lumenal determinants. Traffic 2008, 9, 951–963.
  75. Wang, D.; Dubois, R.N. Eicosanoids and cancer. Nat. Rev. Cancer 2010, 10, 181–193.
  76. Hishikawa, D.; Hashidate, T.; Shimizu, T.; Shindou, H. Diversity and function of membrane glycerophospholipids generated by the remodeling pathway in mammalian cells. J. Lipid Res. 2014, 55, 799–807.
  77. Gyamfi, D.; Ofori Awuah, E.; Owusu, S. Chapter 2—Lipid Metabolism: An Overview. In The Molecular Nutrition of Fats; Patel, V.B., Ed.; Academic Press: Cambridge, MA, USA, 2019; pp. 17–32.
  78. DeBerardinis, R.J.; Lum, J.J.; Hatzivassiliou, G.; Thompson, C.B. The biology of cancer: Metabolic reprogramming fuels cell growth and proliferation. Cell Metab. 2008, 7, 11–20.
  79. Vander Heiden, M.G.; Cantley, L.C.; Thompson, C.B. Understanding the Warburg effect: The metabolic requirements of cell proliferation. Science 2009, 324, 1029–1033.
  80. Zhao, L.; Vogt, P.K. Helical domain and kinase domain mutations in p110alpha of phosphatidylinositol 3-kinase induce gain of function by different mechanisms. Proc. Natl. Acad. Sci. USA 2008, 105, 2652–2657.
  81. Leontiadou, H.; Galdadas, I.; Athanasiou, C.; Cournia, Z. Insights into the mechanism of the PIK3CA E545K activating mutation using MD simulations. Sci. Rep. 2018, 8, 15544.
  82. Gkeka, P.; Evangelidis, T.; Pavlaki, M.; Lazani, V.; Christoforidis, S.; Agianian, B.; Cournia, Z. Investigating the structure and dynamics of the PIK3CA wild-type and H1047R oncogenic mutant. PLoS Comput. Biol. 2014, 10, e1003895.
  83. Ikenoue, T.; Kanai, F.; Hikiba, Y.; Obata, T.; Tanaka, Y.; Imamura, J.; Ohta, M.; Jazag, A.; Guleng, B.; Tateishi, K.; et al. Functional analysis of PIK3CA gene mutations in human colorectal cancer. Cancer Res. 2005, 65, 4562–4567.
  84. Kang, S.; Bader, A.G.; Vogt, P.K. Phosphatidylinositol 3-kinase mutations identified in human cancer are oncogenic. Proc. Natl. Acad. Sci. USA 2005, 102, 802–807.
  85. Bader, A.G.; Kang, S.; Vogt, P.K. Cancer-specific mutations in PIK3CA are oncogenic in vivo. Proc. Natl. Acad. Sci. USA 2006, 103, 1475–1479.
  86. Dogruluk, T.; Tsang, Y.H.; Espitia, M.; Chen, F.; Chen, T.; Chong, Z.; Appadurai, V.; Dogruluk, A.; Eterovic, A.K.; Bonnen, P.E.; et al. Identification of Variant-Specific Functions of PIK3CA by Rapid Phenotyping of Rare Mutations. Cancer Res. 2015, 75, 5341–5354.
  87. Rohrig, F.; Schulze, A. The multifaceted roles of fatty acid synthesis in cancer. Nat. Rev. Cancer 2016, 16, 732–749.
  88. Snaebjornsson, M.T.; Janaki-Raman, S.; Schulze, A. Greasing the Wheels of the Cancer Machine: The Role of Lipid Metabolism in Cancer. Cell Metab. 2020, 31, 62–76.
  89. Georgescu, M.M.; Kirsch, K.H.; Akagi, T.; Shishido, T.; Hanafusa, H. The tumor-suppressor activity of PTEN is regulated by its carboxyl-terminal region. Proc. Natl. Acad. Sci. USA 1999, 96, 10182–10187.
  90. Papa, A.; Wan, L.; Bonora, M.; Salmena, L.; Song, M.S.; Hobbs, R.M.; Lunardi, A.; Webster, K.; Ng, C.; Newton, R.H.; et al. Cancer-associated PTEN mutants act in a dominant-negative manner to suppress PTEN protein function. Cell 2014, 157, 595–610.
  91. Rashmi, R.; DeSelm, C.; Helms, C.; Bowcock, A.; Rogers, B.E.; Rader, J.L.; Rader, J.; Grigsby, P.W.; Schwarz, J.K. AKT inhibitors promote cell death in cervical cancer through disruption of mTOR signaling and glucose uptake. PLoS ONE 2014, 9, e92948.
  92. Leslie, N.R.; den Hertog, J. Mutant PTEN in Cancer: Worse Than Nothing. Cell 2014, 157, 527–529.
  93. Salmena, L.; Carracedo, A.; Pandolfi, P.P. Tenets of PTEN tumor suppression. Cell 2008, 133, 403–414.
  94. Choi, S.W.; Lee, Y.; Shin, K.; Koo, H.; Kim, D.; Sa, J.K.; Cho, H.J.; Shin, H.M.; Lee, S.J.; Kim, H.; et al. Mutation-specific non-canonical pathway of PTEN as a distinct therapeutic target for glioblastoma. Cell Death Dis. 2021, 12, 374.
  95. Kloosterhof, N.K.; Bralten, L.B.; Dubbink, H.J.; French, P.J.; van den Bent, M.J. Isocitrate dehydrogenase-1 mutations: A fundamentally new understanding of diffuse glioma? Lancet Oncol. 2011, 12, 83–91.
  96. Clark, O.; Yen, K.; Mellinghoff, I.K. Molecular Pathways: Isocitrate Dehydrogenase Mutations in Cancer. Clin. Cancer Res. 2016, 22, 1837–1842.
  97. Dang, L.; White, D.W.; Gross, S.; Bennett, B.D.; Bittinger, M.A.; Driggers, E.M.; Fantin, V.R.; Jang, H.G.; Jin, S.; Keenan, M.C.; et al. Cancer-associated IDH1 mutations produce 2-hydroxyglutarate. Nature 2010, 465, 966.
  98. Shim, E.H.; Livi, C.B.; Rakheja, D.; Tan, J.; Benson, D.; Parekh, V.; Kho, E.Y.; Ghosh, A.P.; Kirkman, R.; Velu, S.; et al. L-2-Hydroxyglutarate: An epigenetic modifier and putative oncometabolite in renal cancer. Cancer Discov. 2014, 4, 1290–1298.
  99. Parker, S.J.; Metallo, C.M. Metabolic consequences of oncogenic IDH mutations. Pharmacol. Ther. 2015, 152, 54–62.
  100. Yang, H.; Ye, D.; Guan, K.L.; Xiong, Y. IDH1 and IDH2 mutations in tumorigenesis: Mechanistic insights and clinical perspectives. Clin. Cancer Res. 2012, 18, 5562–5571.
  101. Reitman, Z.J.; Jin, G.; Karoly, E.D.; Spasojevic, I.; Yang, J.; Kinzler, K.W.; He, Y.; Bigner, D.D.; Vogelstein, B.; Yan, H. Profiling the effects of isocitrate dehydrogenase 1 and 2 mutations on the cellular metabolome. Proc. Natl. Acad. Sci. USA 2011, 108, 3270–3275.
  102. Esmaeili, M.; Hamans, B.C.; Navis, A.C.; van Horssen, R.; Bathen, T.F.; Gribbestad, I.S.; Leenders, W.P.; Heerschap, A. IDH1 R132H mutation generates a distinct phospholipid metabolite profile in glioma. Cancer Res. 2014, 74, 4898–4907.
  103. Zhou, L.; Wang, Z.; Hu, C.; Zhang, C.; Kovatcheva-Datchary, P.; Yu, D.; Liu, S.; Ren, F.; Wang, X.; Li, Y.; et al. Integrated Metabolomics and Lipidomics Analyses Reveal Metabolic Reprogramming in Human Glioma with IDH1 Mutation. J. Proteome Res. 2019, 18, 960–969.
  104. Dumbrava, E.I.; Meric-Bernstam, F. Personalized cancer therapy-leveraging a knowledge base for clinical decision-making. Cold Spring Harb. Mol. Case Stud. 2018, 4, a001578.
  105. Hudes, G.; Carducci, M.; Tomczak, P.; Dutcher, J.; Figlin, R.; Kapoor, A.; Staroslawska, E.; Sosman, J.; McDermott, D.; Bodrogi, I.; et al. Temsirolimus, interferon alfa, or both for advanced renal-cell carcinoma. N. Engl. J. Med. 2007, 356, 2271–2281.
  106. Motzer, R.J.; Escudier, B.; Oudard, S.; Hutson, T.E.; Porta, C.; Bracarda, S.; Grunwald, V.; Thompson, J.A.; Figlin, R.A.; Hollaender, N.; et al. Efficacy of everolimus in advanced renal cell carcinoma: A double-blind, randomised, placebo-controlled phase III trial. Lancet 2008, 372, 449–456.
  107. Benjamin, D.; Colombi, M.; Moroni, C.; Hall, M.N. Rapamycin passes the torch: A new generation of mTOR inhibitors. Nat. Rev. Drug Discov. 2011, 10, 868–880.
  108. Blair, H.A. Duvelisib: First Global Approval. Drugs 2018, 78, 1847–1853.
  109. Markham, A. Alpelisib: First Global Approval. Drugs 2019, 79, 1249–1253.
  110. Dhillon, S. Ivosidenib: First Global Approval. Drugs 2018, 78, 1509–1516.
  111. Katso, R.; Okkenhaug, K.; Ahmadi, K.; White, S.; Timms, J.; Waterfield, M.D. Cellular function of phosphoinositide 3-kinases: Implications for development, homeostasis, and cancer. Annu. Rev. Cell Dev. Biol. 2001, 17, 615–675.
  112. Engelman, J.A.; Luo, J.; Cantley, L.C. The evolution of phosphatidylinositol 3-kinases as regulators of growth and metabolism. Nat. Rev. Genet. 2006, 7, 606–619.
  113. Courtney, K.D.; Corcoran, R.B.; Engelman, J.A. The PI3K pathway as drug target in human cancer. J. Clin. Oncol. 2010, 28, 1075–1083.
  114. Fruman, D.A.; Chiu, H.; Hopkins, B.D.; Bagrodia, S.; Cantley, L.C.; Abraham, R.T. The PI3K Pathway in Human Disease. Cell 2017, 170, 605–635.
  115. Cheung, L.W.; Yu, S.; Zhang, D.; Li, J.; Ng, P.K.; Panupinthu, N.; Mitra, S.; Ju, Z.; Yu, Q.; Liang, H.; et al. Naturally occurring neomorphic PIK3R1 mutations activate the MAPK pathway, dictating therapeutic response to MAPK pathway inhibitors. Cancer Cell 2014, 26, 479–494.
  116. Seton-Rogers, S. Signalling: Uncovering new functions of PI3K mutations. Nat. Rev. Cancer 2014, 14, 766–767.
  117. Moukarzel, L.A.; Da Cruz Paula, A.; Ferrando, L.; Hoang, T.; Sebastiao, A.P.M.; Pareja, F.; Park, K.J.; Jungbluth, A.A.; Capella, G.; Pineda, M.; et al. Clonal relationship and directionality of progression of synchronous endometrial and ovarian carcinomas in patients with DNA mismatch repair-deficiency associated syndromes. Mod. Pathol. 2021, 34, 994–1007.
  118. Sun, M.; Hillmann, P.; Hofmann, B.T.; Hart, J.R.; Vogt, P.K. Cancer-derived mutations in the regulatory subunit p85alpha of phosphoinositide 3-kinase function through the catalytic subunit p110alpha. Proc. Natl. Acad. Sci. USA 2010, 107, 15547–15552.
  119. Li, X.; Lau, A.Y.T.; Ng, A.S.N.; Aldehaiman, A.; Zhou, Y.; Ng, P.K.S.; Arold, S.T.; Cheung, L.W.T. Cancer-associated mutations in the p85alpha N-terminal SH2 domain activate a spectrum of receptor tyrosine kinases. Proc. Natl. Acad. Sci. USA 2021, 118, e2101751118.
  120. Deng, L.; Wang, C.; Spencer, E.; Yang, L.; Braun, A.; You, J.; Slaughter, C.; Pickart, C.; Chen, Z.J. Activation of the IkappaB kinase complex by TRAF6 requires a dimeric ubiquitin-conjugating enzyme complex and a unique polyubiquitin chain. Cell 2000, 103, 351–361.
  121. Pickart, C.M. Ubiquitin in chains. Trends Biochem. Sci. 2000, 25, 544–548.
  122. Spence, J.; Gali, R.R.; Dittmar, G.; Sherman, F.; Karin, M.; Finley, D. Cell cycle-regulated modification of the ribosome by a variant multiubiquitin chain. Cell 2000, 102, 67–76.
  123. Huen, M.S.; Grant, R.; Manke, I.; Minn, K.; Yu, X.; Yaffe, M.B.; Chen, J. RNF8 transduces the DNA-damage signal via histone ubiquitylation and checkpoint protein assembly. Cell 2007, 131, 901–914.
  124. Mukhopadhyay, D.; Riezman, H. Proteasome-independent functions of ubiquitin in endocytosis and signaling. Science 2007, 315, 201–205.
  125. Yumimoto, K.; Akiyoshi, S.; Ueo, H.; Sagara, Y.; Onoyama, I.; Ueo, H.; Ohno, S.; Mori, M.; Mimori, K.; Nakayama, K.I. F-box protein FBXW7 inhibits cancer metastasis in a non-cell-autonomous manner. J. Clin. Investig. 2015, 125, 621–635.
  126. Yeh, C.H.; Bellon, M.; Nicot, C. FBXW7: A critical tumor suppressor of human cancers. Mol. Cancer 2018, 17, 115.
  127. Close, V.; Close, W.; Kugler, S.J.; Reichenzeller, M.; Yosifov, D.Y.; Bloehdorn, J.; Pan, L.; Tausch, E.; Westhoff, M.A.; Dohner, H.; et al. FBXW7 mutations reduce binding of NOTCH1, leading to cleaved NOTCH1 accumulation and target gene activation in CLL. Blood 2019, 133, 830–839.
  128. Koepp, D.M.; Schaefer, L.K.; Ye, X.; Keyomarsi, K.; Chu, C.; Harper, J.W.; Elledge, S.J. Phosphorylation-dependent ubiquitination of cyclin E by the SCFFbw7 ubiquitin ligase. Science 2001, 294, 173–177.
  129. Oberg, C.; Li, J.; Pauley, A.; Wolf, E.; Gurney, M.; Lendahl, U. The Notch intracellular domain is ubiquitinated and negatively regulated by the mammalian Sel-10 homolog. J. Biol. Chem. 2001, 276, 35847–35853.
  130. Yada, M.; Hatakeyama, S.; Kamura, T.; Nishiyama, M.; Tsunematsu, R.; Imaki, H.; Ishida, N.; Okumura, F.; Nakayama, K.; Nakayama, K.I. Phosphorylation-dependent degradation of c-Myc is mediated by the F-box protein Fbw7. EMBO J. 2004, 23, 2116–2125.
  131. Wei, W.; Jin, J.; Schlisio, S.; Harper, J.W.; Kaelin, W.G., Jr. The v-Jun point mutation allows c-Jun to escape GSK3-dependent recognition and destruction by the Fbw7 ubiquitin ligase. Cancer Cell 2005, 8, 25–33.
  132. Mao, J.H.; Kim, I.J.; Wu, D.; Climent, J.; Kang, H.C.; DelRosario, R.; Balmain, A. FBXW7 targets mTOR for degradation and cooperates with PTEN in tumor suppression. Science 2008, 321, 1499–1502.
  133. Inuzuka, H.; Shaik, S.; Onoyama, I.; Gao, D.; Tseng, A.; Maser, R.S.; Zhai, B.; Wan, L.; Gutierrez, A.; Lau, A.W.; et al. SCF(FBW7) regulates cellular apoptosis by targeting MCL1 for ubiquitylation and destruction. Nature 2011, 471, 104–109.
  134. Liu, X.; Wang, L.; Zhao, K.; Thompson, P.R.; Hwang, Y.; Marmorstein, R.; Cole, P.A. The structural basis of protein acetylation by the p300/CBP transcriptional coactivator. Nature 2008, 451, 846–850.
  135. Delvecchio, M.; Gaucher, J.; Aguilar-Gurrieri, C.; Ortega, E.; Panne, D. Structure of the p300 catalytic core and implications for chromatin targeting and HAT regulation. Nat. Struct. Mol. Biol. 2013, 20, 1040–1046.
  136. Pao, G.M.; Janknecht, R.; Ruffner, H.; Hunter, T.; Verma, I.M. CBP/p300 interact with and function as transcriptional coactivators of BRCA1. Proc. Natl. Acad. Sci. USA 2000, 97, 1020–1025.
  137. Chan, H.M.; Krstic-Demonacos, M.; Smith, L.; Demonacos, C.; La Thangue, N.B. Acetylation control of the retinoblastoma tumour-suppressor protein. Nat. Cell Biol. 2001, 3, 667–674.
  138. Grossman, S.R. p300/CBP/p53 interaction and regulation of the p53 response. Eur. J. Biochem. 2001, 268, 2773–2778.
  139. Friedrichs, N.; Jager, R.; Paggen, E.; Rudlowski, C.; Merkelbach-Bruse, S.; Schorle, H.; Buettner, R. Distinct spatial expression patterns of AP-2alpha and AP-2gamma in non-neoplastic human breast and breast cancer. Mod. Pathol. 2005, 18, 431–438.
  140. Salloum, R.; McConechy, M.K.; Mikael, L.G.; Fuller, C.; Drissi, R.; DeWire, M.; Nikbakht, H.; De Jay, N.; Yang, X.; Boue, D.; et al. Characterizing temporal genomic heterogeneity in pediatric high-grade gliomas. Acta Neuropathol. Commun. 2017, 5, 78.
  141. Shi, D.; Pop, M.S.; Kulikov, R.; Love, I.M.; Kung, A.L.; Grossman, S.R. CBP and p300 are cytoplasmic E4 polyubiquitin ligases for p53. Proc. Natl. Acad. Sci. USA 2009, 106, 16275–16280.
  142. Fahraeus, R.; Olivares-Illana, V. MDM2’s social network. Oncogene 2014, 33, 4365–4376.
  143. Klein, A.M.; de Queiroz, R.M.; Venkatesh, D.; Prives, C. The roles and regulation of MDM2 and MDMX: It is not just about p53. Genes Dev. 2021, 35, 575–601.
  144. Attar, N.; Kurdistani, S.K. Exploitation of EP300 and CREBBP Lysine Acetyltransferases by Cancer. Cold Spring Harb. Perspect. Med. 2017, 7, a026534.
  145. Pasqualucci, L.; Dominguez-Sola, D.; Chiarenza, A.; Fabbri, G.; Grunn, A.; Trifonov, V.; Kasper, L.H.; Lerach, S.; Tang, H.; Ma, J.; et al. Inactivating mutations of acetyltransferase genes in B-cell lymphoma. Nature 2011, 471, 189–195.
  146. Peifer, M.; Fernandez-Cuesta, L.; Sos, M.L.; George, J.; Seidel, D.; Kasper, L.H.; Plenker, D.; Leenders, F.; Sun, R.; Zander, T.; et al. Integrative genome analyses identify key somatic driver mutations of small-cell lung cancer. Nat. Genet. 2012, 44, 1104–1110.
  147. Merk, D.J.; Ohli, J.; Merk, N.D.; Thatikonda, V.; Morrissy, S.; Schoof, M.; Schmid, S.N.; Harrison, L.; Filser, S.; Ahlfeld, J.; et al. Opposing Effects of CREBBP Mutations Govern the Phenotype of Rubinstein-Taybi Syndrome and Adult SHH Medulloblastoma. Dev. Cell 2018, 44, 709–724.e706.
  148. Mondello, P.; Tadros, S.; Teater, M.; Fontan, L.; Chang, A.Y.; Jain, N.; Yang, H.; Singh, S.; Ying, H.Y.; Chu, C.S.; et al. Selective Inhibition of HDAC3 Targets Synthetic Vulnerabilities and Activates Immune Surveillance in Lymphoma. Cancer Discov. 2020, 10, 440–459.
  149. Deng, L.; Meng, T.; Chen, L.; Wei, W.; Wang, P. The role of ubiquitination in tumorigenesis and targeted drug discovery. Signal Transduct. Target. Ther. 2020, 5, 11.
  150. Lu, G.; Middleton, R.E.; Sun, H.; Naniong, M.; Ott, C.J.; Mitsiades, C.S.; Wong, K.K.; Bradner, J.E.; Kaelin, W.G., Jr. The myeloma drug lenalidomide promotes the cereblon-dependent destruction of Ikaros proteins. Science 2014, 343, 305–309.
  151. Stewart, A.K. Medicine. How thalidomide works against cancer. Science 2014, 343, 256–257.
  152. Fricker, L.D. Proteasome Inhibitor Drugs. Annu. Rev. Pharmacol. Toxicol. 2020, 60, 457–476.
  153. Dick, L.R.; Fleming, P.E. Building on bortezomib: Second-generation proteasome inhibitors as anti-cancer therapy. Drug Discov. Today 2010, 15, 243–249.
  154. Nelson, W.J.; Nusse, R. Convergence of Wnt, beta-catenin, and cadherin pathways. Science 2004, 303, 1483–1487.
  155. Gattinoni, L.; Zhong, X.S.; Palmer, D.C.; Ji, Y.; Hinrichs, C.S.; Yu, Z.; Wrzesinski, C.; Boni, A.; Cassard, L.; Garvin, L.M.; et al. Wnt signaling arrests effector T cell differentiation and generates CD8+ memory stem cells. Nat. Med. 2009, 15, 808–813.
  156. Petersen, C.P.; Reddien, P.W. Wnt signaling and the polarity of the primary body axis. Cell 2009, 139, 1056–1068.
  157. Spranger, S.; Gajewski, T.F. A new paradigm for tumor immune escape: Beta-catenin-driven immune exclusion. J. Immunother. Cancer 2015, 3, 43.
  158. Junge, H.J. Ligand-Selective Wnt Receptor Complexes in CNS Blood Vessels: RECK and GPR124 Plugged In. Neuron 2017, 95, 983–985.
  159. Miyoshi, Y.; Nagase, H.; Ando, H.; Horii, A.; Ichii, S.; Nakatsuru, S.; Aoki, T.; Miki, Y.; Mori, T.; Nakamura, Y. Somatic mutations of the APC gene in colorectal tumors: Mutation cluster region in the APC gene. Hum. Mol. Genet. 1992, 1, 229–233.
  160. Fearnhead, N.S.; Britton, M.P.; Bodmer, W.F. The ABC of APC. Hum. Mol. Genet. 2001, 10, 721–733.
  161. Azzopardi, D.; Dallosso, A.R.; Eliason, K.; Hendrickson, B.C.; Jones, N.; Rawstorne, E.; Colley, J.; Moskvina, V.; Frye, C.; Sampson, J.R.; et al. Multiple rare nonsynonymous variants in the adenomatous polyposis coli gene predispose to colorectal adenomas. Cancer Res. 2008, 68, 358–363.
  162. Pai, S.G.; Carneiro, B.A.; Mota, J.M.; Costa, R.; Leite, C.A.; Barroso-Sousa, R.; Kaplan, J.B.; Chae, Y.K.; Giles, F.J. Wnt/beta-catenin pathway: Modulating anticancer immune response. J. Hematol. Oncol. 2017, 10, 101.
  163. Imperial, R.; Ahmed, Z.; Toor, O.M.; Erdogan, C.; Khaliq, A.; Case, P.; Case, J.; Kennedy, K.; Cummings, L.S.; Melton, N.; et al. Comparative proteogenomic analysis of right-sided colon cancer, left-sided colon cancer and rectal cancer reveals distinct mutational profiles. Mol. Cancer 2018, 17, 177.
  164. Ficari, F.; Cama, A.; Valanzano, R.; Curia, M.C.; Palmirotta, R.; Aceto, G.; Esposito, D.L.; Crognale, S.; Lombardi, A.; Messerini, L.; et al. APC gene mutations and colorectal adenomatosis in familial adenomatous polyposis. Br. J. Cancer 2000, 82, 348–353.
  165. Mihalatos, M.; Danielides, I.; Belogianni, J.; Harokopos, E.; Papadopoulou, E.; Kalimanis, G.; Tsiava, M.; Triantafillidis, J.K.; Kosmidis, P.A.; Fountzilas, G.; et al. Novel mutations of the APC gene in familial adenomatous polyposis in Greek patients. Cancer Genet. Cytogenet. 2003, 141, 65–70.
  166. Kitagawa, M.; Hatakeyama, S.; Shirane, M.; Matsumoto, M.; Ishida, N.; Hattori, K.; Nakamichi, I.; Kikuchi, A.; Nakayama, K.; Nakayama, K. An F-box protein, FWD1, mediates ubiquitin-dependent proteolysis of beta-catenin. EMBO J. 1999, 18, 2401–2410.
  167. Kikuchi, A. Tumor formation by genetic mutations in the components of the Wnt signaling pathway. Cancer Sci. 2003, 94, 225–229.
  168. Morin, P.J.; Sparks, A.B.; Korinek, V.; Barker, N.; Clevers, H.; Vogelstein, B.; Kinzler, K.W. Activation of beta-catenin-Tcf signaling in colon cancer by mutations in beta-catenin or APC. Science 1997, 275, 1787–1790.
  169. Rubinfeld, B.; Robbins, P.; El-Gamil, M.; Albert, I.; Porfiri, E.; Polakis, P. Stabilization of beta-catenin by genetic defects in melanoma cell lines. Science 1997, 275, 1790–1792.
  170. Liu, C.; Li, Y.; Semenov, M.; Han, C.; Baeg, G.H.; Tan, Y.; Zhang, Z.; Lin, X.; He, X. Control of beta-catenin phosphorylation/degradation by a dual-kinase mechanism. Cell 2002, 108, 837–847.
  171. Rebouissou, S.; Franconi, A.; Calderaro, J.; Letouze, E.; Imbeaud, S.; Pilati, C.; Nault, J.C.; Couchy, G.; Laurent, A.; Balabaud, C.; et al. Genotype-phenotype correlation of CTNNB1 mutations reveals different ss-catenin activity associated with liver tumor progression. Hepatology 2016, 64, 2047–2061.
  172. Tu, J.; Park, S.; Yu, W.; Zhang, S.; Wu, L.; Carmon, K.; Liu, Q.J. The most common RNF43 mutant G659Vfs*41 is fully functional in inhibiting Wnt signaling and unlikely to play a role in tumorigenesis. Sci. Rep. 2019, 9, 18557.
  173. Hao, H.X.; Xie, Y.; Zhang, Y.; Charlat, O.; Oster, E.; Avello, M.; Lei, H.; Mickanin, C.; Liu, D.; Ruffner, H.; et al. ZNRF3 promotes Wnt receptor turnover in an R-spondin-sensitive manner. Nature 2012, 485, 195–200.
  174. Koo, B.K.; Spit, M.; Jordens, I.; Low, T.Y.; Stange, D.E.; van de Wetering, M.; van Es, J.H.; Mohammed, S.; Heck, A.J.; Maurice, M.M.; et al. Tumour suppressor RNF43 is a stem-cell E3 ligase that induces endocytosis of Wnt receptors. Nature 2012, 488, 665–669.
  175. UniProt, C. UniProt: The universal protein knowledgebase in 2021. Nucleic Acids Res. 2021, 49, D480–D489.
  176. Spit, M.; Fenderico, N.; Jordens, I.; Radaszkiewicz, T.; Lindeboom, R.G.; Bugter, J.M.; Cristobal, A.; Ootes, L.; van Osch, M.; Janssen, E.; et al. RNF43 truncations trap CK1 to drive niche-independent self-renewal in cancer. EMBO J. 2020, 39, e103932.
  177. Anastas, J.N.; Moon, R.T. WNT signalling pathways as therapeutic targets in cancer. Nat. Rev. Cancer 2013, 13, 11–26.
  178. Jung, Y.S.; Park, J.I. Wnt signaling in cancer: Therapeutic targeting of Wnt signaling beyond beta-catenin and the destruction complex. Exp. Mol. Med. 2020, 52, 183–191.
  179. Hori, K.; Sen, A.; Artavanis-Tsakonas, S. Notch signaling at a glance. J. Cell Sci. 2013, 126, 2135–2140.
  180. Bray, S.J. Notch signalling in context. Nat. Rev. Mol. Cell Biol. 2016, 17, 722–735.
  181. Siebel, C.; Lendahl, U. Notch Signaling in Development, Tissue Homeostasis, and Disease. Physiol. Rev. 2017, 97, 1235–1294.
  182. Pancewicz, J.; Taylor, J.M.; Datta, A.; Baydoun, H.H.; Waldmann, T.A.; Hermine, O.; Nicot, C. Notch signaling contributes to proliferation and tumor formation of human T-cell leukemia virus type 1-associated adult T-cell leukemia. Proc. Natl. Acad. Sci. USA 2010, 107, 16619–16624.
  183. Yeh, C.H.; Bellon, M.; Pancewicz-Wojtkiewicz, J.; Nicot, C. Oncogenic mutations in the FBXW7 gene of adult T-cell leukemia patients. Proc. Natl. Acad. Sci. USA 2016, 113, 6731–6736.
  184. Oswald, F.; Tauber, B.; Dobner, T.; Bourteele, S.; Kostezka, U.; Adler, G.; Liptay, S.; Schmid, R.M. p300 acts as a transcriptional coactivator for mammalian Notch-1. Mol. Cell Biol. 2001, 21, 7761–7774.
  185. Wallberg, A.E.; Pedersen, K.; Lendahl, U.; Roeder, R.G. p300 and PCAF act cooperatively to mediate transcriptional activation from chromatin templates by notch intracellular domains in vitro. Mol. Cell Biol. 2002, 22, 7812–7819.
  186. Huang, Y.H.; Cai, K.; Xu, P.P.; Wang, L.; Huang, C.X.; Fang, Y.; Cheng, S.; Sun, X.J.; Liu, F.; Huang, J.Y.; et al. CREBBP/EP300 mutations promoted tumor progression in diffuse large B-cell lymphoma through altering tumor-associated macrophage polarization via FBXW7-NOTCH-CCL2/CSF1 axis. Signal Transduct. Target. Ther. 2021, 6, 10.
  187. Majumder, S.; Crabtree, J.S.; Golde, T.E.; Minter, L.M.; Osborne, B.A.; Miele, L. Targeting Notch in oncology: The path forward. Nat. Rev. Drug Discov. 2021, 20, 125–144.
  188. Pannuti, A.; Foreman, K.; Rizzo, P.; Osipo, C.; Golde, T.; Osborne, B.; Miele, L. Targeting Notch to target cancer stem cells. Clin. Cancer Res. 2010, 16, 3141–3152.
  189. Takebe, N.; Nguyen, D.; Yang, S.X. Targeting notch signaling pathway in cancer: Clinical development advances and challenges. Pharmacol. Ther. 2014, 141, 140–149.
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