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Metadichol-Induced KLF Expression in PBMC Cells. Links SIRTs, NRs, TLRs, and Circadian genes. A Systems-Wide Biology Approach

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04 February 2025

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05 February 2025

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Abstract

Metadichol expresses all nuclear receptors, the TLR family (1-10), the Sirtuin family (1-7), all 48 nuclear receptors, and all Yamanaka factors: Oct 4, Sox2, KLF4, C-myc, and circadian genes: Per1, CRY1, BMAL1, CLOCK, and PPARGC1A. The transcription factor family Kruppel-like factors (KLFs) is essential for cell proliferation, differentiation, and development. Our tiny chemical, Metadichol, a long-chain lipid alcohol nanoemulsion, modulates KLF family 1-18 expression. Concentration dependent. At 1 ng/ml, 16 of 18 KLF transcription factors are downregulated, save KLF 4 and 18. Small chemical modulators of KLF expression and activity offer new therapeutic approaches for many disorders, including cancer. In immunotherapy, KLF10 inhibition may reduce T regulatory cell numbers or function to boost anti-tumor immunity. Small compounds substituting KLF4 in cellular reprogramming could increase iPSC production efficiency and safety in regenerative medicine. In addition to KLF family expression results, this research will examine the regulation mechanisms of KLFs, nuclear receptors, SIRTs, circadian genes, Toll-like receptors, Klotho, P53, and PPARGC1A in cancer. These protein families form a dynamic web of interconnected signaling networks that affect cancer biology, including the mechanisms of crosstalk between them, the roles of individual members in different cancer types, and the tumor microenvironment's effect on these interactions. Our research reveals that molecular biology, genetics, immunology, and clinical oncology must be integrated to understand cancer's intricate networks. This will allow novel therapeutic techniques to target gene family connections, improving cancer therapy results and tumor biology understanding.

Keywords: 
Metadichol KLF
;  
Toll-like receptors
;  
nuclear receptors
;  
Sirtuins
;  
Circadian genes
;  
Klotho
;  
TP53
;  
telomerase
;  
long-chain lipid alcohols
Subject: 
Biology and Life Sciences  -   Biochemistry and Molecular Biology

Introduction

We have 18 mammalian Kruppel-like factor KLFs [1]. The (KLF) family of zinc-finger transcription factors regulates several biological processes. KLFs regulate cell differentiation, proliferation, and development in response to environmental stress. The intricate role of KLFs in many cellular processes emphasizes their importance in homeostasis and their therapeutic potential.

KLF Structure and Classification

KLF proteins have a conserved C-terminal DNA-binding domain. The three C2H2 zinc fingers in this domain allow KLFs to bind to GC-rich DNA [2]. The N-terminal regulatory domains vary, contributing to family members' different roles [2]. The Sp/KLF family includes Sp1-4 and many Kruppel-like factors [3]. These factors bind to Sp1 sites—GC boxes, CACCC boxes, and basic transcription elementswith different affinities [4]. The DNA-binding domain's structural conservation and the N-terminal regulation domain's diversity allow for particular DNA binding and various functional activities.

KLFs and Development Roles

KLFs regulate germ layer formation and body axis patterning during embryonic development. The Xenopus studies show KLF involvement in these processes [5,6]. KLF4 controls important developmental signals [5]. Zebrafish KLF genes regulate hematopoiesis, blood vessel function, fin and epidermal growth. Multiple KLFs' tissue-specific expression patterns in tree shrews highlight their different developmental roles [7]. MMP9 regulation by KLF5 is necessary for cartilage and bone formation [8]. Impaired cartilage breakdown delays bone regeneration in KLF5+/- mice [8]. KLFs' spatiotemporal expression during development shows their exact functions in tissue architecture and function.
Obesity, cardiovascular disease, cancer, and inflammatory disorders are linked to KLF expression dysregulation [1]. KLFs have important roles in renal fibrosis progression, tubulointerstitial inflammation regulation, and glomerular filtration barrier maintenance [9]. Inflammatory monocyte differentiation requires KLF4 [10]. KLF4 -/- chimeras have fewer resident and circulating inflammatory monocytes [10]. KLF10 controls colonic macrophages and DSS colitis risk [11]. KLF10-deficient animals produce less IL-10 and fewer colonic macrophages [11]. They also produce higher IL-12p70 after LPS [11]. KLFs are crucial to optimal physiological function due to their role in these different disease processes (Figure 1).

KLFs in Cancer

Cell growth and cancer progression are heavily regulated by KLFs [3]. They participate in many growth signal transduction pathways. Their overexpression can boost or hinder proliferation. KLFs affect oncogenes and tumor suppressors. They can even cause cancer. Multiple cancers have altered KLF expression. In gastric cancer, KLF8 is associated with poor prognosis [12]. It controls glycolysis via GLUT4 [12]. Higher KLF8 expression in gastric cancer is associated with larger tumors, advanced T and N stages, and shorter survival. Different forms of cancer are linked to KLF8 [12]. Its silencing slows cancer cell glycolysis. The context-dependent activities of KLFs in cancer highlight their intricacy in carcinogenesis.

Immune System and KLFs

KLFs are essential for immune cell growth and function. Inflammatory monocyte differentiation requires KLF4 [10]. KLF2 modulates chemokine receptor patterns to control T-cell trafficking and recirculation [13]. KLF10 controls intestinal macrophages and causes innate immune colitis [11]. Aortic lesions are more extensive in KLF2+/− ApoE−/− animals than in controls [14]. This shows KLF2 protects against atherosclerosis [14]. KLF2 expression is downregulated in monocytes from severe atherosclerosis patients. In endothelial and monocyte cells, KLF2 and KLF4 control shear-dependent genes [14]. The various actions of KLFs on immune cells show their role in innate and adaptive immunity.

Targeting KLFs Therapeutically

KLFs are attractive therapeutic targets due to their involvement in several illnesses. Modulating KLF expression or activity may treat cardiovascular disease, cancer, and inflammatory illnesses [1]. For instance, statins increase endothelium KLF expression, which protects against atherosclerosis [15]. Overexpression of KLF4 prevents atherothrombosis, pulmonary hypertension, and restenosis [1]. KLF13 deficiency in uterine endometrial cells impairs steroid hormone receptor signaling in a mouse model of endometriosis [16]. KLF9 null endometrium increases ectopic lesion formation in the same model [15]. Manipulating KLF activity offers promising treatment approaches to several disorders.

KLFs and Cellular Processes

KLFs control proliferation, apoptosis, differentiation, and stem cell maintenance. [1] KLF4 and KLF5 regulate esophageal cancer cell growth, apoptosis, and invasion. KLF5 promotes invasion, while KLF4 suppresses proliferation and induces apoptosis [17]. KLF4 and KLF5 inhibit esophageal cancer [18]. Colorectal cancer tumor suppression by KLF6 [18]. In colon cancer cells, insulin promotes FASN expression and proliferation [19]. These essential cellular mechanisms demonstrate KLFs' role in tissue homeostasis and cell destiny regulation.

Genetic Regulation via KLFs

KLFs regulate gene expression by binding to DNA [19]. KLF1 is needed for proper globin synthesis [20,21]. KLF4 turns on HBG gene expression in primary erythroid cells [22]. KLF4 preferentially binds to the HBG promoter CACCC region and interacts with CREBBP [22]. In mice, KLF13 controls axonal growth, development, and regeneration [23]. Psychiatric symptoms and ADHD [23] were linked to a de novo heterozygous KLF13 gene variation. KLF5 transactivates MMP9 to degrade cartilage [8]. Adult corticospinal axon regeneration is promoted by KLF7 [23]. Overexpression of VP16-KLF7 stimulates adult mouse CST axon sprouting [24] and regeneration. Figure 1 summarizezs the role of the KLF family of genes in several cellular and physiological processes by regulating the expression of various target genes.

Cross-Regulation and KLF Family Interactions

Cross-regulation between KLF family members complicates their regulatory networks. After arterial damage, KLF4 inhibits neointimal development [14]. It accomplishes this by working against NF-κB [25]. KLF7 indicates aggressive gastric cancer with bad prognosis [26]. KLF family members interact to add control to their regulatory roles.
Metadichol, a long-chain alcohol nanoemulsion [27]. Our prior study [28,29,30,31,32] indicated that Sirtuins, Klotho, Tp53, Telomerase (Tert), FoxO1, PPARGC1A, TLR family, nuclear receptors, Yamanaka factors (Oct 4, KLF2, c-MYC, Sox2), and circadian genes must be expressed and controlled to target cancer. We demonstrate for the first time that Metadichol, a nano formulation of long-chain alcohols, can express and regulate all KLF family members in PBMC cells using Q-RT-PCR at doses from 1 picogram to 100 nanograms.

Experimental

All work was outsourced to Skanda Labs, Bangalore, India. Saha Biologics, Hyderabad, India, supplied all primers.

Isolation of Human WBCs by Cell Line and Condition

Blood sample preparation: Fresh human blood was taken in EDTA tubes, diluted 1:1 with PBS, and mixed by inverting.
Isolation of Mononuclear Cells- In a 15 ml centrifuge tube, 5 ml of Histopaque-1077 was added and 5 ml of prepared blood was progressively put on top without disturbing it. Tubes were then centrifuged at 400 X g for 30 min at room temperature with brake off. Upper layer was removed using Pasteur pipette without disrupting interphase layer after centrifugation. The interphase layer was carefully placed in a clean centrifuge tube. After washing with 1X PBS, cells will be centrifuged at 250 X g for 10 min. (2X). After centrifugation, supernatant was discarded and pellet was recovered in 10% FBS-RPMI medium. Hemo-cytometers counted and verified cell viability.
Cell maintenance and seeding: 1 X 106 cells/ml medium were sown into 6 well plates and incubated for 24 h at 37oC with 5% CO2. After 24 hours of seeding, the medium was carefully removed, and cells were treated with MTT-selected concentrations and kept at 37℃ in a CO2 incubator for 24 hours.
Table 1. Treatment concentrations.
Table 1. Treatment concentrations.
Cell line Sample name Treatment details
Human PBMC Metadichol Control
1 pg/ml
100 pg/ml
1 ng/ml
100ng/ml

Sample Preparation and RNA Isolation

We detached and washed treated cells with sterile 1X PBS and centrifuged. Decant the supernatant and add 0.1 ml of TRIzol, mixing gently by inversion for 1 min. Samples rested at room temperature for 10 minutes. Per 0.1 ml of TRIzol, 0.75 ml chloroform was added. The contents vortexed for 15 seconds. The tube rested at room temperature for 5 minutes. The mixture was centrifuged at 12,000 rpm for 15 minutes at 4˚C. The upper aqueous phase was placed in a sterile micro-centrifuge tube, added 0.25 ml of isopropanol, and incubated at -20˚C for 20 minutes. The contents were centrifuged at 12,000 rpm for 10 minutes at 4˚C. The RNA pellet was rinsed with 0.25 ml of 70% ethanol after discarding supernatant. The RNA mixture was centrifuged at 12,000 rpm at 4˚C. Supernatant was carefully eliminated and pellet air-dried. Re-suspend the RNA pellet in 20 µl of DEPC-treated water. Total RNA yield was measured by Spectra drop (Spectramax i3x, Molecular Devices, USA).

cDNA Production

According to the manufacturer's instructions, 500 ng of RNA was used to synthesize cDNA using Prime script RT reagent kit (TAKARA) and oligo dT primer. A 20 μl reaction volume was used for cDNA synthesis at 50°C for 30 min, followed by RT inactivation at 85°C for 5 min utilizing Veritii biosystems. Real-time PCR was performed on cDNA.

RT-qPCR Primers and Analysis

The PCR mixture (final volume 20 µl) included 1.4 µl cDNA, 10 µL SyBr green Master solution, and 1 µM complementary forward and reverse primers (table 3) for target genes. Enzyme activation at 95°C for 2 minutes was followed by a 2-step reaction with initial denaturation and an annealing cum extension step at 95°C for 5 seconds, annealing for 30 seconds at the appropriate temperature amplified for 39 cycles, secondary denaturation at 95°C for 5 seconds, and 1 cycle with melt curve capture step from 65°C to 95°C for 5 seconds each. Results were examined, and fold expression or regulation was estimated using CFX Maestro software. The comparative CT approach was utilized to compare target gene expression to β-actin and untreated control cells.
The delta CT for each therapy was computed using a formula.
(CT Method)
The comparative CT approach compared target gene expression to β-actin and untreated control cells.
Delta CT was determined for each treatment using the formula.
Delta Ct = target gene – reference gene.
Ct was subtracted from control to get delta delta CT to compare treated samples to untreated controls. Delta delta Ct = treatment group – control group.
Each treatment's target gene expression fold change was estimated using the formula. Fold change = 2^(−delta delta Ct)

Results

Q-RT-PCR (Table 2) showed that at 1 ng/ml, all transcription factors except KLF4, KLF15, KLF 17, and 18 were downregulated or repressed. These findings imply metadichol may be important in various malignancies. According to the literature, many KLF family members are oncogenic. [1] These techniques could treat cancer by suppressing oncogenic gene expression. KLF4, a Yamanaka factor, is increased in fibroblasts and primary cancer cells and is an anticancer agent and cell reprogramming. Figure 5 and Figure 6 show various KLF factor functions in cancer.
The experimental results (Table 4) and literature-based results (Figure 5 and Figure 6) are well correlated. In esophageal cancer, KLF4 expression [33] decreases and KLF5 expression increases [34]. .Metadichol enhanced KLF4 expression at one nanogram per ml and decreased KLF5 expression, as seen in Table 4. In bladder cancer, Metadichol raises KLF4 expression and downregulates KLF5 and KLF6 expression at 100 ng/ml, as indicated in Table 4 and Figure 5 and 6. .The third example is ovarian cancer, where KLF8 expression is elevated (Table 1) and decreased [35] This is important to combat ovarian cancer expression. We can compare our experimental results to those in the literature.[36,37,38,39,40]
By activating the PI3K/AKT pathway, KLF1 promotes cervical cancer dissemination and invasion [41,42].
The tumor suppressor KLF2 is found in breast, colorectal, gastric, and lung malignancies. PI3K/AKT and HIF-1α/Notch-1 pathways are regulated to limit proliferation, invasion, and metastasis [43].
Based on the kind of cancer, KLF3 has two functions. It suppresses and promotes colorectal, lung, cervical, pancreatic, and prostate cancers [44].
Context-dependent dual role for KLF4. In some cases, it increases esophageal squamous cell carcinoma but suppresses colorectal, stomach, and lung malignancies [45].
KLF5 works as a tumor suppressor and promoter depending on cancer type and stage. It affects breast, pancreatic, colorectal, gastric, and endometrial cancers [46].
In prostate cancer, glioblastoma, hepatocellular carcinoma, and lung cancer, KLF6 suppresses tumor growth. A KLF6-SV1 splice variation promotes metastasis [47].
KLF7 is an oncogene in colon, pancreatic, and high-grade serous ovarian cancers [48].
In breast, colorectal, gastric, and liver malignancies, KLF8 promotes proliferation, invasion, and metastasis [49].
KLF9 suppresses breast, pancreatic, hepatocellular, and colorectal cancer growth and metastasis [50].
KLF10 suppresses pancreatic, leukemia, and cervical cancers. In certain cancers, it inhibits growth and induces apoptosis. [51]
In lung, pancreatic, breast, and ovarian cancers, KLF11 plays two roles. In certain situations, it promotes or suppresses cancers [52].
KLF12 increases proliferation and suppresses apoptosis in breast cancer, acting as an oncogene [53].
KLF13 suppresses prostate cancer but may promote other cancers [54].
In breast, colon, and cervical malignancies, KLF14 suppresses tumor growth via the PI3K/AKT pathway [55].
KLF15 suppresses breast, colorectal, and gastric cancer proliferation and metastasis [56].
Oncogene KLF16 promotes proliferation and invasion in breast, bladder, gastric, and pancreatic adenocarcinoma [57].
KLF17 regulates EMT and metastasis to suppress breast, lung, gastric, and esophageal cancers [58].
KLF18's role in cancer is unknown.
The Table 4 and Figure 5 and Figure 6 above imply that targeting all Krüppel-like factor (KLF) family members in cancer therapy may have several benefits:

Antitumor Synergy

Targeting several KLFs can have synergistic antitumor effects due to their different cancer progression functions [59,60]. Different KLFs influence cancer growth, apoptosis, metastasis, and stemness.

Past Compensatory Mechanisms

Targeting one KLF may result in family compensation because KLFs commonly overlap. Inhibiting numerous KLFs simultaneously can overcome compensatory processes and improve treatment efficacy.

Multiple Signaling Pathway Modulation

KLFs regulate key cancer formation pathways like NF-κB, PI3K/AKT, and WNT [61]. Targeting multiple KLFs disrupts oncogenic pathways better than targeting one.

Addressing Tumor Heterogeneity

Cancer subtypes and even cells within the same tumor may depend on various KLFs for survival and progression. A multi-KLF targeting method may address heterogeneity and provide a more holistic therapeutic plan.

Making therapy more effective

Pancreatic cancer treatment resistance, especially radioresistance, is linked to KLFs like KLF10 [62]. Targeting these KLFs with other family members may improve therapy efficacy and overcome resistance.

Potential for Personalized Medicine

KLF expression and roles vary by cancer type and patient [3,12].. Based on a patient's tumor's KLF expression profile, targeting various KLFs provides for a more personalized strategy.
Targeting numerous KLF family genes in cancer treatment may be promising, however KLFs also regulate cellular activities and homeostasis [8].
Genetic and epigenetic changes throughout cancer genesis and progression cause uncontrolled cell proliferation and metastasis. This complex process involves several molecular regulators with unique but interrelated roles. In cancer, we must study the synergistic interactions between Kruppel-like factors (KLFs), sirtuins, Toll-like receptors (TLRs), nuclear receptors, circadian clocks, Klotho, p53, and TERT. They each contribute to cancer etiology, but more crucially, their complicated interconnections determine their synergistic effects. Understanding these complex interactions is essential for creating new cancer treatments.
We previously demonstrated that somatic cell lines express all sirtuins toll receptors nuclear receptors circadian transcription factors , Klotho TP53 , and telomerase [28,29,30,31,32,63,64,65]. Figure 7, Figure 8, Figure 9 and Figure 10 show how sirtuins, TLRs, and nuclear receptors affect cancer.

KLF and Regulatory Pathway Interactions

Complex diseases characterized by uncontrolled cell growth and spread involve intricate interactions between signaling pathways and regulatory molecules and four key protein families in cancer: Kruppel-like factors (KLFs), nuclear receptors (NRs), sirtuins, and Toll-like receptors.
The Klf and Sirtuin families regularly influence cancer-related pathways. Their effects on metabolic processes, especially glycolysis, overlap [66,67,68]. As previously discussed, cancer cells often modify glycolysis, a key metabolic process, to facilitate their uncontrolled growth and survival. Both families affect EMT [69,70], a crucial cancer metastatic mechanism. Additionally, the Klf and Sirtuin families regulate cell cycle and apoptosis [65,66], affecting tumor growth and cell survival.
Klf and sirtuin proteins may interact synergistically or antagonistically due to common regulatory mechanisms. These interactions may rely on the Klf and Sirtuin members and cellular environment. For instance, a tumor suppressor Klf protein could work with sirtuin to limit tumor growth. Conversely, an oncogenic Klf protein and sirtuin may stimulate tumor growth. Klf, a tumor suppressor, could oppose an oncogenic sirtuin, creating a complicated interaction that affects cancer formation. These interactions are complex and require further study to understand their effects on cancer.
Klf and Sirtuin activities rely on cell type, tissue microenvironment, and other signaling molecules [71,72,73]. This explains the seemingly contradicting literature, where the same protein can be a tumor suppressor and an oncogene. For instance, the same Klf protein can prevent tumor growth in one cancer cell but increase it in another.
NRs ( figure 10) interact with many signaling pathways dysregulated in cancer. [74]. This interaction greatly complicates cancer genesis and progression. For instance, ERs interact with the PI3K/AKT pathway, which controls cell growth and survival. This connection boosts cell proliferation and survival, promoting tumor growth. ARs affect cell cycle progression and apoptosis via many signaling pathways. PRs regulate uterine and mammary gland cell proliferation and differentiation. [74]. NRs' functional interaction with various signaling pathways is context-dependent, contributing to cancer formation and progression heterogeneity.

Established KLF-NR Interactions in Cancer

Several investigations have shown direct physical interactions between specific KLFs and NRs, though the field is still evolving. In endometrial epithelial cells, KLF9 interacts with PR isoforms A and B. [74]. KLF9 directly modulates PR transcription and affects PR target genes implicated in cancer development and progression. [75] KLFs may directly influence NR activity, affecting cancer-related NR target gene expression. However, direct interactions between other KLFs and NRs are understudied, providing a promising study topic.
KLFs and NRs can influence each other through shared signaling pathways and regulatory networks without direct physical contact. [76,77,78,79,80,81]. KLFs can indirectly affect NR activity by regulating NR or co-regulator expression. Conversely, NRs can regulate KLF expression or activity. This complicated interaction provides regulatory loops that fine-tune gene expression and shape cellular response to inputs. This intricate interaction affects cancer growth and progression, making it an essential research field.

KLF-TLR Interactions in Cancer

There is some evidence that KLFs directly regulate TLR expression, however this is not well documented. Studies have suggested that KLFs regulate TLR gene transcription [82] to determine which KLF isoforms are involved, which TLR genes they target, and the molecular processes of this control. Identification of KLF-binding sites in TLR gene promoters would prove this regulation.
KLFs and TLRs may indirectly affect downstream targets like inflammatory cytokines. Both KLFs and TLRs regulate NF-κB, a transcription factor crucial for inflammation and cancer. NF-κB activation causes pro-inflammatory cytokines to promote tumor development and angiogenesis [83,84,85,86]. The convergence of KLF and TLR signaling on NF-κB is a critical interaction site that affects cancer formation. Further research into the processes of this convergence is needed to completely comprehend KLF-TLR interactions in cancer.
KLF-TLR interactions are especially important during macrophage polarization. TLRs, essential components of the innate immune system, initiate immunological responses and shape the TME. TLR stimulation drives macrophage polarization toward the pro-inflammatory M1 phenotype, while KLF4, a major regulator of macrophage polarization, can balance M1 and M2 phenotypes. [87] TLR-mediated activation and KLF4-mediated macrophage polarization affect TME and cancer progression
PTEN-deficient prostate cancer cells express TLR3, TLR4, and TLR9 differently [88]. PTEN, a tumor suppressor gene, controls cell growth and survival. PTEN-deficient cells express TLRs differently, suggesting they may be involved in prostate cancer growth. The relationship between TLRs and KLFs in prostate cancer needs additional study. This interaction may reveal prostate cancer growth and progression processes. KLF modulation of TLR expression and signaling in prostate cancer cells needs further study to completely grasp this connection. The effect of this interaction on treatment response needs additional study.
According to breast cancer study, TLR3 signaling increases IL-6 and STAT3 phosphorylation [88]. Both IL-6 and STAT3, a transcription factor important in cell proliferation and survival, increase cancer progression. This shows that TLR3 signaling promotes breast cancer growth and inflammation. In cancer, KLFs and TLRs affect TME inflammation and immunological responses [89,90,91,92,93,94,95,96].

Cancer, KLFs, and Circadian Clock

KLFs, core circadian genes (CRY1, PER1, CLOCK, BMAL1), and PPARG1CA (peroxisome proliferator-activated receptor gamma coactivator 1 alpha) play intricate functions in cancer pathways. The circadian clock, a crucial timekeeping mechanism, is increasingly implicated in cancer development and progression [97,98,99]. PPARG1CA, a key regulator of energy metabolism and lipid homeostasis, influences cellular processes like inflammation, cell proliferation, and apoptosis [100]. A key transcriptional coactivator, PPARG1CA regulates energy metabolism and lipid homeostasis [101]. This function is closely linked to PPARγ, a nuclear receptor involved in several metabolic processes. By increasing the transcriptional activity of PPARγ, PPARG1CA improves its effects on gene expression. This coactivator regulates glucose, lipid, mitochondrial, and adipogenesis genes. Through its effects on inflammation, cell proliferation, and apoptosis, PPARG1CA dysregulation may contribute to many malignancies. PPARG1CA's involvement in cancer varies by type and tumor microenvironment. PPARG1CA can prevent or accelerate tumor development. Its effects on inflammation, a cancer driver, are important. PPARG1CA affects the tumor microenvironment via modulating inflammatory cytokines and signaling pathways. Its regulation of cell proliferation and apoptosis also affects cancer cell growth and survival. More research is needed to understand PPARG1CA's various effects in different cancer types and situations.
Circadian clocks and KLFs interact through complicated regulatory networks. KLF10's liver rhythmic expression, depending on BMAL1, a circadian clock component, is a good illustration of this connection [102,103]. This regulatory link shows the circadian clock regulates KLF activity and cancer pathways. KLF10's rhythmic expression may help maintain liver metabolic homeostasis[104] by coordinating hepatic metabolic activities. Circadian clock dysfunction can disrupt this rhythmic expression, causing metabolic abnormalities and metabolic-associated malignancies.
KLF10 is not the only circadian gene-KLF relationship. Other KLF isoforms may be regulated by the circadian clock through complex transcriptional and post-transcriptional processes. KLFs may also affect circadian gene expression, producing feedback loops that regulate cellular functions.[105]
The complicated relationship between circadian genes and KLF10 in hepatic metabolism [104] shows this context dependence. KLF10's rhythmic expression depends on BMAL1, but other factors may potentially affect it, resulting in different consequences. These synergistic and antagonistic interactions will determine cancer pathway effects.
Understanding how circadian genes and KLFs affect cancer growth and progression opens new treatment possibilities. These parameters may be modulated to reduce tumor development, improve therapy efficacy, or improve patient outcomes [102,103,104,105,106].

KLF-TP53, TERT, FOXO1, Klotho Interactions in Cancer

KLFs like KLF4 and KLF5 directly interact with TP53 to boost its tumor suppressor function. These interactions can synergistically promote apoptosis and decrease cell growth [105,106,107] The mechanisms of these interactions are still being studied, but transcriptional control and protein-protein interactions are presumably involved. To develop new cancer therapeutics targeting TP53-KLF pathways, these interactions must be understood.
The link between KLFs and TERT is unclear. However, indirect interactions are possible because KLFs regulate cell growth and senescence, and TERT maintains cancer cell telomeres. KLFs may indirectly affect cancer cell telomerase activity and length by modulating TERT expression or activity.

Interactions between KLF and FOXO1 in Cancer Pathways Are Complex

Many studies show a complex relationship between KLFs and FOXO1. [108]. KLFs like KLF4 may complement FOXO1 to prevent tumor growth by inducing apoptosis and reducing cell proliferation. Other KLFs may interact with FOXO1 antagonistically, encouraging tumor development.
These genes' critical involvement in controlling cancer pathways make them intriguing cancer therapy targets. Strategies to restore tumor suppressor KLFs or inhibit oncogenic KLFs are being studied. Gene therapy or small molecule inhibitors may be used. Modulating TP53, TERT, or FOXO1 activity may also be helpful.

Klotho-KLF Interactions in Cancer: An Indirect Influence Network

Since Klotho and KLF proteins are involved in several cancer-relevant pathways, indirect interactions are likely. Direct physical interactions are not yet known. Klotho and other KLFs modulate signaling cascades, including IGF-1, Wnt/β-catenin, and TGF-β pathways [109,110,111]. Klotho and KLFs may interact functionally and crosstalk in cancer due to their overlapping regulatory impact. [112,113] These interactions may vary by KLF family member, malignancy kind, and cellular microenvironment.

Synergistic and Antagonistic Effects: Context-Dependent Results

Based on the situation, Klotho and KLFs can synergistically or antagonistically affect cancer pathways. Klotho's inhibitory action on Wnt/β-catenin signaling may boost the synergistic anti-cancer effects of KLFs targeting this pathway. [114,115,116] This intricate interaction emphasizes the importance of KLF and cancer type for predicting Klotho and KLF effects on cancer progression. [117,118,119]
Klotho and KLF family member expression levels may be cancer biomarkers. [120]. Low Klotho expression or activity often indicates a worse prognosis and more aggressive tumors. Specific KLF expression patterns [120,121,122] can predict tumor behavior and patient survival.Klotho and KLFs are promising therapeutic targets due to their cancer pathway functions. Strategies to restore Klotho expression or activity may help malignancies with downregulated Klotho. (109,110)
Inputting all the genes expressed by Metadichol into the STRING database network analysis program [123] shows literature-curated interactions between and relationships of the gene families.
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Figure 11. KLF, NR, TLR, Sirtuins, and circadian family gene network connections.
Figure 11. KLF, NR, TLR, Sirtuins, and circadian family gene network connections.
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Figure 12. Metadichol gene expression and its impact on cancer processes .
Figure 12. Metadichol gene expression and its impact on cancer processes .
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Conclusions

Metadichol has the capacity to affect various molecular families implicated in cancer formation and progression (figure 12) and offers a unique potential for cancer research and treatment. This multidimensional approach may be able to target numerous cancer hallmarks, outperforming single-pathway therapies.
Metadichol's capacity to regulate several actors in the complex and dynamic interaction of these molecular families in cancer presents interesting new cancer treatment possibilities. Metadichol can now be used to treat many cancers due to its nontoxicity [124,125,126].

Declarations

Nanorx, Inc.'s R&D budget provided funding. The author is a major shareholder in Nanorx Inc., NY, USA, the author founded the company.

Author Contributions

PPR designed and supervised the work and is entirely responsible for its content. All data are in the manuscript. Supplementary raw data is available on request.

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Figure 1. Diseases and KLFs.
Figure 1. Diseases and KLFs.
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Figure 5. KLF and expression levels in malignancies.
Figure 5. KLF and expression levels in malignancies.
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Figure 6. Klf expression levels in various malignancies.
Figure 6. Klf expression levels in various malignancies.
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Figure 7. Sirtuin expressions in cancer.
Figure 7. Sirtuin expressions in cancer.
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Figure 8. TLRs oncogenic role.
Figure 8. TLRs oncogenic role.
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Figure 9. TLRs anti-tumor effects.
Figure 9. TLRs anti-tumor effects.
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Figure 10. Nuclear Receptors in Cancer.
Figure 10. Nuclear Receptors in Cancer.
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Table 2. RNA yields.
Table 2. RNA yields.
Test concentrations
RNA yield (ng/µl) 0 1 pg/ ml 100 pg/ ml 1 ng/ ml 100 ng/ ml
Human PBMC's 623.120 343.123 792.123 673.111 611.123
Table 3. Primer details.
Table 3. Primer details.
Primer Sequence Amplicon size Annealing temperature
GAPDH GTCTCCTCTGACTTCAACAGCG 186 60
ACCACCCTGTTGCTGTAGCCAA
KLF1 CAGGTGTGATAGCCGAGACC 111 65
TCTTGGTGTAGCTCTTGCCG
KLF2 CCAAGAGTTCGCATCTGAAGGC 131 65
CCGTGTGCTTTCGGTAGTGGC
KLF3 CTCATGGTCTCCTTATCGGAGG 131 65
TGTCCTCTGTGGTTCGATCCCA
KLF4 CCTTCCTGCCCGATCAGATG 132 62
TGAGCATCATCCCGTGTGTC
KLF5 GGAGAAACGACGCATCCACTAC 140 65
GAACCTCCAGTCGCAGCCTTC
KLF6 GACAGCTCCGAGGAACTTTCT 156 65
CACGCAACCCCACAGTTGA
KLF7 CTCACGAGGCACTACAGGAAAC 135 67
TGGCAACTCTGGCCTTTCGGTT
KLF8 CCTGAAAGCTCACCGCAGAATC 113 61
TGCTTGCGGAAATGGCGAGTGA
KLF9 GGGAAACACGCCTCCGAAAA 110 65
CGTTCACCTGTATGCACTCTGTA
KLF10 AGGAGTCACATCTGTAGCCACC 139 67
GAACGGGCAAACCTCCTTTCAC
KLF11 ATGGATGCAGCCACACCTGAAC 115 65
GGAGAAACAGGTGTCCTTGTCG
KLF12 CCTTTCCATAGCCAGAGCAGTAC 130 65
CTGGCGTCTTGTGCTCTCAATAC
KLF13 CAGAGGAAGCACAAGTGCCACT 137 65
CGCGAACTTCTTGTTGCAGTCC
KLF14 CATCCAGATATGATCGAGTACCG 163 65
CCTTGAGGGTAAGACTGACAGC
KLF15 GTGAGAAGCCCTTCGCCTGCA 114 67
ACAGGACACTGGTACGGCTTCA
KLF16 GACTGCGCCAAAGCCTACTACA 171 65
CCTGCCAGTCACAAGCAAAAGG
KLF17 GCTGCCCAGGATAACGAGAAC 128 67
ATCTCTGCGCTGTGAGGAAAG
KLF18 TCCATGGGCCAGAAAGTGAC 197 67
GGGTGTTCAGCTGGCTACTT
Table 4. Metadichol-induced expression of various KLF family members.
Table 4. Metadichol-induced expression of various KLF family members.
Control 1 pg/ml 100 pg/ml 1 ng/ml 100 ng/ml
KLF1 1 1.42 0.94 0.22 0.7
KLF2 1 1.03 0.67 0.27 0.77
KLF3 1 1.63 1.35 0.38 1.35
KLF4 1 1.1 0.24 1.56 0.8
KLF5 1 0.98 0.7 0.3 0.96
KLF6 1 0.57 0.54 0.46 0.47
KLF7 1 0.87 0.5 0.12 1.02
KLF8 1 4.99 0.85 0.34 1.02
KLF9 1 3.02 1.3 0.41 1.08
KLF10 1 1.4 1.38 0.26 1.15
KLF11 1 1.45 1.5 0.28 0.91
KLF12 1 0.59 0.76 0.22 0.88
KLF13 1 1.84 0.92 0.27 1.12
KLF14 1 1.45 1.05 0.32 1.51
KLF15 1 2.9 1.49 0.89 2.14
KLF16 1 2.31 1.47 0.36 0.93
KLF17 1 0.39 0.41 0.66 2.47
KLF18 1 1.23 0.87 1.75 1.91
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