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202434 上海市同济医院

International Journal of Biological Macromolecules 260 (2024) 129635Available online 22 January 20240141-8130/© 2024 Published by Elsevier B.V.Glycolysis related lncRNA SNHG3 / miR-139-5p / PKM2 axis promotes castration-resistant prostate cancer (CRPC) development and enzalutamide resistance Yicong Yao a,b,1, Xi Chen a,b,1, Xin'an Wang a,b,1, Haopeng Li a,b, Yaru Zhu a,b, Xilei Li b, Zhihui Xiao b, Tong Zi a,b, Xin Qin a,b, Yan Zhao a,b, Tao Yang a,b, Licheng Wang a,*, Gang Wu a,*, Xia Fang ... [收起]
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第1页

International Journal of Biological Macromolecules 260 (2024) 129635

Available online 22 January 2024

0141-8130/© 2024 Published by Elsevier B.V.

Glycolysis related lncRNA SNHG3 / miR-139-5p / PKM2 axis promotes

castration-resistant prostate cancer (CRPC) development and

enzalutamide resistance

Yicong Yao a,b,1

, Xi Chen a,b,1

, Xin'an Wang a,b,1

, Haopeng Li a,b

, Yaru Zhu a,b

, Xilei Li b

,

Zhihui Xiao b

, Tong Zi a,b

, Xin Qin a,b

, Yan Zhao a,b

, Tao Yang a,b

, Licheng Wang a,*

, Gang Wu a,*

,

Xia Fang c,*

, Denglong Wu a,*

a Department of Urology, Tongji Hospital, School of Medicine, Tongji University, Shanghai 200065, China b School of Medicine, Tongji University, Shanghai 200092, China c Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai, China

ARTICLE INFO

Keywords:

Glycolysis

CRPC

LncRNA-SNHG3

miR-139-5p

PKM2

ABSTRACT

Although androgen deprivation therapy (ADT) by the anti-androgen drug enzalutamide (Enz) may improve the

survival level of patients with castration-resistant prostate cancer (CRPC), most patients may eventually fail due

to the acquired resistance. The reprogramming of glucose metabolism is one type of the paramount hallmarks of

cancers. PKM2 (Pyruvate kinase isozyme typeM2) is a speed-limiting enzyme in the glycolytic mechanism, and

has high expression in a variety of cancers. Emerging evidence has unveiled that microRNAs (miRNAs) and long

non-coding RNAs (lncRNAs) have impact on tumor development and therapeutic efficacy by regulating PKM2

expression. Herein, we found that lncRNA SNHG3, a highly expressed lncRNA in CRPC via bioinformatics

analysis, promoted the invasive ability and the Enz resistance of the PCa cells. KEGG pathway enrichment

analysis indicated that glucose metabolic process was tightly correlated with lncRNA SNHG3 level, suggesting

lncRNA SNHG3 may affect glucose metabolism. Indeed, glucose uptake and lactate content determinations

confirmed that lncRNA SNHG3 promoted the process of glycolysis. Mechanistic dissection demonstrated that

lncRNA SNHG3 facilitated the advance of CRPC by adjusting the expression of PKM2. Further explorations

unraveled the role of lncRNA SNHG3 as a ‘sponge’ of miR-139-5p and released its binding with PKM2 mRNA,

leading to PKM2 up-regulation. Together, Our studies suggest that lncRNA SNHG3 / miR-139-5p / PKM2

pathway promotes the development of CRPC via regulating glycolysis process and provides valuable insight into

a novel therapeutic approach for the disordered disease.

1. Introduction

Prostate cancer (PCa) is one kind of the highest incidence cancers,

and the second leading cause of cancer-associated deaths in males [1].

The development of PCa cells is mainly driven by androgen receptor

(AR) so that inhibition of AR activity by androgen-deprivation therapy

(ADT) can successfully prevent disease progression [2]. Nevertheless,

PCa benefits from ADT treatment for only 2 to 3 years and it will

eventually develop to the castration-resistant prostate cancer (CRPC)

[3]. ADT is ineffective for CRPC, which results that tumors can grow in a

low androgenic environment [4,5]. In addition, the incidence of

metastatic CRPC has steadily increased in recent years [6], and CRPC

primarily leads to bone metastases [7]. Since the nosogenesis of CRPC

has not been fully articulated up to now, the identification of CRPC

therapeutic targets is therefore a research hotspot in this area [8,9].

The energy metabolism of tumor cells differs from that of normal

ones. Tumor cells utilize glycolysis instead of aerobic respiration as the

metabolic mode to generate energy, leading to the eventual conversion

of the glucose into lactate [10,11]. This metabolic change is one kind of

the biochemical features of cancer cells, which is also known as the

Warburg effect [11,12]. A body of studies has confirmed that Warburg

effect plays a vital role in the advance of CRPC [13–15].

* Corresponding authors.

E-mail addresses: 1911633@tongji.edu.cn (L. Wang), wg_urologist@163.com (G. Wu), dilay_110@126.com (X. Fang), wudenglong2009@tongji.edu.cn (D. Wu). 1 These authors contributed equally.

Contents lists available at ScienceDirect

International Journal of Biological Macromolecules

journal homepage: www.elsevier.com/locate/ijbiomac

https://doi.org/10.1016/j.ijbiomac.2024.129635

Received 23 May 2023; Received in revised form 11 December 2023; Accepted 22 December 2023

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International Journal of Biological Macromolecules 260 (2024) 129635

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Most glycolysis-related genes including the rate-limiting enzymes are

highly expressed in tumor tissues [10,16]. PKM2 (Pyruvate kinase

isozyme type M2) is a key speed-limiting enzyme in the glycolytic

mechanism. The last rate-limiting step of glycolysis pathway was catalyzed by the conversion of phosphoenolpyruvate (PEP) to pyruvate by

PKM2 [17–19]. PKM2 is highly expressed in a variety of cancers, which

included prostate cancer [14,17,20,21]. PKM2 induces the multiplication, migration and invasion of tumor cells to accelerate tumor development [22,23]. Recent evidence has displayed that microRNAs

(miRNAs) and long non-coding RNAs (lncRNAs) can influence tumor

development and therapeutic efficacy by regulating PKM2 expression

[24–26], which is one of the most important pathways for PKM2 to exert

its biological effects [27,28]. However, PKM2 based the regulatory

network in PCa is still elusive and open to investigate.

LncRNAs are one category of non-coding RNAs over 200 nt in length

that are drawn into the adjustment of various biological processes [29].

Increasing evidence demonstrates that lncRNAs play a crucial role via

different mechanisms in the pathogenesis of cancers [30]. LncRNAs can

also be in connection with the regulation of target gene expression and

have a tight correlation with the proliferation, immune infiltration,

metastasis and prognosis of CRPC [31–33].

Small nucleolar RNA host gene 3 (SNHG3), situated at chromosome

1p35 with 2.3 kb nucleotides, is a typical lncRNA that was recently

identified [34]. It has been observed to be upregulated in various cancers and to be involved in a variety of tumorigenesis as a critical regulator [35–37]. However, there were few reports about the role that

lncRNA-SNHG3 played in the advancement of PCa [38]. As is known

to all, miRNAs play a vital role as a ‘bridge’ connecting lncRNA and

targeting mRNA. In this study, miR-139-5p was forecasted by StarBase

software to be the miRNA with multiple binding sites of lncRNA-SNHG3

and PKM2. miR-139-5P has been documented as a crucial adjuster of

several tumors, including gallbladder carcinoma, pancreatic cancer and

colorectal cancer [39–41]. However, its role in PCa development is

largely unknown.

Our study indicate that lncRNA-SNHG3/ miR-139-5p / PKM2 axis

may be an effective metabolism target for anti-PCa therapy.

2. Methods and materials

2.1. Cell culture and Enz-resistant cell lines C4–2R generation

C4–2, the human PCa cell line with Enz sensitive, was procured from

American Type Culture Collection (ATCC, Manassas, VA). The C4–2 cell

line was cultured in RPMI 1640 medium without androgen, then

increasing Enz (Beyotime, SC0074, Nantong, China) concentration to

10 μM, and then to 20 μM, and to 40μM finally. C4–2 cell line was

cultured with a gradient of the aforementioned concentrations for 30

days each and eventually develop to the C4–2 Enz resistant cell line

(C4–2R). The concentration of Enz which the cells maintained was

10μM. 22RV1, another kind of Enz resistant PCa cells, was cultured in

1640 medium as well.

2.2. 13C –Metabolic Flux analysis of cancer cells

Prostate cancer tumor cells C4–2 and C4–2R were incubated in 1640

medium (no glucose) with 2 g/L U-13C glucose for half an hour. The

supernatant culture medium was eliminated and the residual culture

medium was washed away with sterilized injection water. The sterilized

injection water was removed and the cells were digested with trypsin,

transferred into centrifuge tubes and centrifuged for 5 min, then washed

with PBS, supernatant removed and quickly submerged in liquid nitrogen for 30 s for snap freezing. The cell centrifuge tubes were removed

and stored in dry ice.

The derivatization of the cells metabolites for GC/MS analysis was

performed by the mass spectrometer. The Peak plots and isotope information of the metabolites were collected through GC/MS analysis to

obtain isotope information of metabolites. Identification of metabolic

pathways, distribution information of the isotopes of each compound

and 13C flux ratio analysis were performed using Matlab flux-8. The 13C

flux ratio of individual metabolites from labelled carbon sources in the

extracellular pathway can be calculated directly. Further changes in

intracellular energy metabolism in tissue samples were traced with 13Cglucose labelling. The Metabolic Flux analysis was carried by Biotree

Biotech (Shanghai, China).

2.3. Western blot

Cells were lysed by utilizing RIPA (Epizyme, Shanghai, China) and

analyzed for total protein concentration by BCA reagent kits (Beyotime,

Nantong, China). Equal quantities of total protein were electrophoresed

on the freshly prepared 10 % SDS-PAGE gels before transferring to PVDF

membranes. After the step of membranes transferring, the membranes

were blocked by the fast blocking liquid (Epizyme, Shanghai, China) for

25 min at room temperature, and then incubated with the primary antibodies at 4 ◦C for 12 h. The antibodies used in this step are shown

below: PKM2 (Proteintech, 15822–1-AP, 1:1,000 dilution), GLUT1

(Affbiotech, AF0173, 1:5,000 dilution), LDHA (Abcam, ab52488,

1:1,000 dilution), HK2 (Abcam, ab209847, 1:1,000 dilution), GAPDH

(Abcam, ab59164, 1:5,000 dilution). And then the membranes were

incubated with the secondary antibodies for 3 h at room temperature,

and finally visualized by ECL system.

2.4. RNA isolation and qPCR

The total RNA was extracted by utilizing Trizol (Sigma, Missouri,

USA). The PrimeScript Kit (Takara, Otsu City, Japan) was utilized to

compound cDNA. Then the qPCR was performed. GAPDH played the

role as the endogenous control. Data were analyzed by utilizing the

2− △△Ct method. The primer sequences were listed as followed: SNHG3

forward (TTCAAGCGATTCTCGTGCC), SNHG3 reverse (AAGATTGTCAAACCCTCCCTGT), GAPDH forward (ACAACTTTGGTATCGTGGAAGG), GAPDH reverse (GCCATCACGCCACAGTTTC), PKM2 forward

(ATGTCGAAGCCCCATAGTGAA), PKM2 reverse (TGGGTGGTGAATCAATGTCCA), miR-139-5p forward (CGCGTCACAGTGCACGTGTC),

miR-139-5p reverse (AGTGCAGGGTCCGAGGTATT), miR-139-5p RT

primer (GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACACTGGA), miR-330-5p forward (GCGTCTCTGGGCCTGTGTC),

miR-330-5p reverse (AGTGCAGGGTCCGAGGTATT), miR-330-5p RT

primer (GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACGCCTAA), miR-326 forward (CGCCTCTGGGCCCTTC), miR326 reverse (AGTGCAGGGTCCGAGGTATT), miR-330-5p RT primer

(GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACCTGGAG), U6 forward (ATTGGAACGATACAGAGAAGATT),

U6 reverse (GGAACGCTTCACGAATTTG).

2.5. Transfection

When the degree of fusion reached 80 %, cells were transfected with

Lipofectamine 2000. The empty vector plasmid was utilized as blank

control. The plasmids were diluted in Opti-MEM (Gibco, California,

USA) and then allowed to sit for 20 min before being added to the medium. The cells were continued to be cultured for 48 h after transfection.

The plasmids were purchased from Fenghui Biotech (Hunan, China).

2.6. Glucose uptake determination

The determination was carried by the glucose content test kit

(BC2505, Solarbio Science & Technology, Beijing, China). The cells were

collected in a centrifuge tube, centrifuged and the supernatant discarded. The cells were diluted at a ratio of 500:1 of cell number: volume

of distilled water (mL), ultrasonically crushed (ice bath, 3 s at 20 % or

200 W, 10 s interval, repeated thirty times), boiled in the boiling water

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International Journal of Biological Macromolecules 260 (2024) 129635

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bath for 15 min, cooled and then centrifuged at 8000 rpm for 10 min, the

supernatant was taken and set aside. The microplate reader was preheated for over half an hour, the wavelength was tuned to 505 nm and

zeroed with distilled water.

The following reagents were added sequentially to the 96-well plate.

Blank tube: 20 μL distilled water +180 μL mixed reagent; Standard tube:

20 μL Reagent I (2 μmol/mL glucose solution) + 180 μL mixed reagent;

Assay tube: 20 μL sample + 180 μL mixed reagent. (Mixed reagent is a

1:1 equal volume mix of Reagent II and Reagent III). The reagents were

mixed before being held at 37 ◦C for 15 min, and finally the absorbance

was surveyed at 505 nm. The absorbance values for the blank, standard

and assay tubes were denoted as A1, A2 and A3 respectively.

Glucose uptake (

μmol/

104 cells)

= (C standard × V1) × (A3 − A1)

÷ (A2 − A1) ÷ (500 × V1 ÷ V2)

= 0.004 × (A3 − A1) ÷ (A2 − A1)

(C Standard: standard tube concentration, 2 μmol/mL; V1: volume of

sample added, 20 μL = 0.02 mL; V2: total sample volume, 1 mL; 500:

total number of cells, 5 million).

2.7. Lactate content determination

The cells were digested and passaged in the same quantities and

cultured in the culture dishes for 48 h. The supernatants were taken

separately and then taken to the EICU of Shanghai Tongji Hospital to

determine the lactate content.

2.8. CCK8 assays

After transfection of the plasmid, the cells were continued to be

cultured for 48 h, then digested and centrifuged, then resuspended. Cells

were added to 96-well plates at 2,000–3,000 cells/well with 200 μL of

cell suspension per well. CCK8 assay was added 10 μL to each well on 0

day, 2 days, 4 days and 6 days after the suspension was added. The

absorbance per well was surveyed at 450 nm after the cells were incubated at 37 ◦C for 4 h.

2.9. Transwell assays

After transfection of the plasmid, the cells were continued to be

cultured for 48 h, then digested and centrifuged before re-suspending in

serum-free medium to remain the density of 1 × 105 cell /mL. The

matrigel was diluted in 1:30 with the serum-free medium, then 100 μL of

diluted matrigel was added to the upper chamber of per transwell

chamber. The chambers were then incubated in a 37 ◦C, 5 % CO2

incubator for 4 h to form the matrigel coating on the surface of the

chambers. 100 μL of cell suspension was added to each upper chamber,

and then 600 μL of complete medium was added to each lower chamber.

The chambers were incubated in a 37 ◦C, 5 % CO2 incubator for 48 h.

The chambers were removed, fixed with formaldehyde for 20 min

and washed with ddH2O. Then the chambers that had been fixed were

stained by 0.2 % crystal violet for 20–25 min before being washed with

ddH2O. Then the cells were observed under the microscope.

2.10. Bioinformatics analysis

Downstream miRNAs of LncRNA SNHG3 and upstream miRNAs of

PKM2 were analyzed by utilizing StarBase databases (http://starbase.

sysu.edu.cn/). The SNHG3 expression data between tumor tissue and

normal prostate tissue were acquired from TCGA (http://gdc.cancer.

gov) databases, and the SNHG3 expression data between CSPC and

CRPC were acquired from GSE35988 dataset in GEO (https://www.ncbi.

nlm.nih.gov/geo/) databases. The KEGG pathway enrichment was

analyzed with the use of Metascape platform (http://metascape.org/gp

/index.html).

2.11. Patients and clinical database

60 PCa patients who underwent radical resection of PCa in Shanghai

Tongji Hospital between 2013 and 2018 were recruited. Patients were

selected according to the following criteria, including 1) confirmation of

pathological diagnosis, 2) absence of postoperative adjuvant anti-cancer

therapy, and 3) review of TNM classification, Gleason scores and PSA

level. The clinical data of each patient were acquired from the admission

records. The subject has been ethically approved by the Medical Ethics

Committee of Shanghai Tongji Hospital. All patients who participated in

this study have provided informed consent.

2.12. Immunohistochemistry

The tumor tissue microarray was built as the above description. The

anti-PKM2 antibody (Proteintech, 15822-1-AP, 1:1,000 dilution) was

used for IHC staining. The staining intensity of the specimen was evaluated by the pathologists who didn't know the clinicopathological data

and the patient's clinical results. The tissue microarray was dewaxed in

xylene solution, then rehydrated with gradient ethanol concentrations,

and then was subjected to antigen repair, followed by blocking of the

inactivated endogenous peroxidase. Then the anti-PKM2 antibody

(diluted 1:1,000) was added, and the microarray was incubated at 4 ◦C

for one night. Then the microarray was incubated for 45mins with

secondary antibody. PKM2 staining intensity was scored on the scales

from 1 to 4, which included 1) 1 (unstained), 2) 2 (weakly stained), 3) 3

(moderately stained) and 4) 4 (strongly stained). Tissues with scores of 3

and 4 were defined as high expression, and those with scores of 1 and 2

were defined as low expression.

2.13. Tumor xenograft

20 of 4-weeks-old male nude mice were purchased and divided into 4

groups randomly. 22RV1 cells that steadily expressing empty vector, shLncRNA SNHG3, sh-PKM2, sh-LncRNA SNHG3 + sh-PKM2 were separately injected subcutaneously under the axillaries of the mice. The

volumes of xenograft were calculated by the following formula: volume

(cm3

) = (length × width2

)/2. All of the mice were performed euthanasia

6 weeks after being injected. After that, the tumor xenografts were

collected and weighed. All procedures for the mouse experiments were

approved by the Animal Care Committee of Shanghai Tongji Hospital.

2.14. Luciferase assay

The human PKM2 3′UTRs containing mutant or wild-type miRNAreactive elements were duplicated into the vector structure at the

downstream of the luciferase. Luciferase activity was determined by

diluciferase assay.

2.15. Pull-down

The cells were lysed by utilizing RIPA. The supernatant fluid was

then mixed with 500 pM of antisense oligonucleotide and RNAase inhibitor was added at 4 ◦C for 12 h. And then the cells were mixed with

10ul of streptavidin agarose beads for 2 h at 4 ◦C and then incubated

with the supernatant for 2 h. After adding 10 μL of streptavidin agarose

beads, the cells were mixed at 4 ◦C for 2 h. Then the streptavidin

sepharose beads were incubated with the liquid supernatant for 2 h. The

complexes were centrifuged at 3500 rpm for 10 min and the beads were

washed for 5 times by utilizing RIPA. The RNA was extracted and subjected to RT-PCR analysis.

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2.16. Fluorescence in situ hybridization (FISH)

The FISH assay was used to detect the location of lncRNA SNHG3 in

PCa cells, besides detect the expression differences of lncRNA SNHG3 in

normal prostate tissues and PCa tissues. The h-SNHG3_FISH Probe Mix

(lnc1100775) was purchased from Guangzhou RiboBio Co., LTD,

(Guangzhou, China). The C4–2 and C4–2R cells were inoculated on the

slides in a 6-well plate and were cultured until the degree of cells fusion

reached about 60–70 %. Then the slides were taken out, washed by PBS

for 5 min and fixed with 4 % formaldehyde for 10 min. Next, FISH was

conducted according to the protocol provided by the kit. Under the

condition of light protection, 2.5uL of 20uM lncRNA FISH Probe Mix

stock solution was added to 100ul of hybridization solution. Each well of

cells was added to 100uL of hybridization solution containing the probe

and was hybridized overnight at 37 ◦C, protected from light. After

stained with DAPI staining solution, the slides were carefully removed

from the wells, fixed with sealer and observed under the fluorescence

microscope. The FISH of tissues was conducted following by the Kit

protocol as well. The tissue sections were provided by the department of

pathology, Shanghai Tongji Hospital, Shanghai, China.

2.17. Statistical analysis

Statistical analysis was performed with GraphPad Prism 8.0. All

values are presented as means ± standard deviation (SD). Student's t-test

was used to determine statistical differences between two groups. And P

< 0.05 was considered statistically significant (*:P < 0.05, **: P < 0.01,

***: P < 0. 001; NS: no significance).

3. Results

3.1. LncRNA SNHG3 is highly expressed in CRPC

SNHG3, confirmed as a typical lncRNA, has been documented to be

involved in multiple tumorigenesis as a regulatory factor. Furthermore,

PRAD in TCGA database were used to analyze the expression level of

lncRNA SNHG3 between PCa tissues and normal controls, the distinctions between the tumor group and the normal group were analyzed

with Student's t-test (Fig. 1A, p = 1.184e-22). The prostate cancerrelated dataset GSE35988 was downloaded from the GEO database for

differential analysis of lncRNA SNHG3 expression levels between CSPC

tissues and CRPC tissues. As shown in Fig. 1B, the expression level of

SNHG3 was significant increased in CRPC as compared to CSPC counterparts (p = 5.4e-3), implying SNHG3 may be a key player of CRPC

development. Enzalutamide induced resistance is a big obstacle of PCa

management.

Fluorescence in situ hybridization (FISH) assay was used to detect

the expression differences of lncRNA SNHG3 in normal prostate tissues

and PCa tissues. Based on the results of Fig. 1C, lncRNA SNHG3

expression in tumor tissues was higher obviously than that in the normal

ones. This result strongly mirrored the finding in the TCGA database

above. Meanwhile, FISH analysis also demonstrated the location of

lncRNA SNHG3 in PCa cells, the results showed that lncRNA SNHG3 was

mainly distributed in cytoplasm of C4–2 and C4–2R cells (Fig. 1D).

RT-PCR analysis was used to verify the differences of lncRNA SNHG3

expression between C4–2 and C4–2R prostate cancer cell lines. The results demonstrated that the expression increased obviously in C4–2R cell

lines (Fig. 1E).

Next, CCK8 and transwell assays were performed to verify the effect

of lncRNA SNHG3 expression on the invasive abilities and the resistance

to Enz of the PCa cells. Firstly, C4–2R cells (with/without knocked-down

LncRNA SNHG3) were subjected to 10μM Enz treatment in the CCK8

experiment. We found that the resistance to Enz of C4–2R decreased

distinctly compared to the vector control group after we knocked down

lncRNA SNHG3. Interestingly, C4–2R cells with knocked-down lncRNA

SNHG3 were still more resistant to Enz than C4–2 (Fig. 1F). Similar

results were found in the transwell assay. The cellular invasion in C4–2R

cells with knocked-down LncRNA SNHG3 decreased apparently

compared with the vehicle control group. By contrast, the cellular invasion in C4–2 cells with overexpression lncRNA SNHG3 decreased

apparently compared to the vector control group (Fig. 1G-H).

In summary, The results revealed that lncRNA SNHG3 was highly

expressed in CRPC and promoted the cell invasion and Enz resistance.

3.2. LncRNA SNHG3 promotes the process of glycolysis

To identify which signaling pathways are highly related to lncRNA

SNHG3 expression, we performed KEGG pathway enrichment analysis of

lncRNA SNHG3 associated genes utilizing Metascape platform(http:

//metascape.org/gp/index.html) (Supplementary File 1). The result

suggested that the glucose metabolic process pathway may be regulated

by lncRNA SNHG3 (Fig. 1I). According to Warburg effect, cancer cells

under aerobic condition tend to metabolize glucose to lactate. Therefore

we performed assays to determine glucose uptake and lactate production in order to verify whether lncRNA SNHG3 participated in the

regulation of glycolysis. The result demonstrated that an increased

consumption of glucose was observed in C4–2 cells when lncRNA

SNHG3 was overexpressed (Fig. 1J). On the contrary, knockdown of

lncRNA SNHG3 reduced the glucose uptake in C4–2R cells (Fig. 1J).

Similarly, lncRNA SNHG3 overexpression elevated lactate production in

C4–2 cells while lncRNA SNHG3 knockdown exerted the opposite effect

towards lactate production in C4–2R cells (Fig. 1K).

In conclusion, lncRNA SNHG3 postively regulates the glycolysis of

PCa.

3.3. PKM2 is highly expressed in enzalutamide resistant PCa

The process of glycolysis was presented in Fig. 2A and there are some

key rate-limiting enzymes that play significant characters in regulating

the speed and rate of glycolysis metabolites production. To explore

whether there is a difference on the glycolysis metabolites between

C4–2R and C4–2, we first performed the 13C –Metabolic Flux analysis. As

revealed in Fig. 2B, the metabolic flux of both glycolysis and TCA in

C4–2R was obviously raised in contrast to that in C4–2 cell lines suggesting chronic enzalutamide treatment promotes glycolysis The similar

results can also be observed from the PCA score plot (Fig. 2C), volcano

plot (Fig. 2D), OPLS-DA permutation histogram (Fig. 2E) and OPLS-DA

permutation plot (Fig. 2F). The phenomenon prompted us to investigate

expression levels of glycolysis related key enzymes between C4–2 and

C4–2R cell lines. Western blot analysis displayed that PKM2 was

remarkably expressed in C4–2R cells as compared to C4–2 controls

(Fig. 2G). Then we would like to explore the protein expression of PKM2

in 22RV1 cells, another PCa cell line which is resistant to Enz, to

improve the experimental universality. Western blot and qPCR analysis

were conducted in C4–2, C4–2R and 22RV1 cells. The result showed that

the PKM2 expression in 22RV1 cells was higher than C4–2 cells, and

similar with C4–2R cells (Fig. 2H). To further corroborate PKM2

expression in PCa, we detected PKM2 expression in PCa tissues using

IHC. We divided PKM2-stained tissue specimens into four groups based

on staining intensity from weak to strong, as shown in Fig. 2I. Data

revealed that the positive signal of PKM2 was correlated with Gleason

scores positively (P = 0.0348; Fig. 2J), tumor stages (P = 0.0005;

Fig. 2K) and PSA levels (P = 0.0312; Fig. 2L), and was no significant

correlation with the presence of metastasis (P = 0.8147; Fig. 2M). These

data suggested that PKM2 might play a vital role in the progression of

PCa.

Collectively, PKM2, as a key rate-limiting enzyme in glycolysis process, is highly expressed in PCa and can be induced upon chronic

enzalutamide treatment.

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3.4. LncRNA SNHG3 promotes development of CRPC by regulating the

expression of PKM2

In order to evaluate whether lncRNA SNHG3 modulates PKM2 in the

C4–2R and C4–2 cells, we conducted qPCR experiments. Results

revealed that the mRNA expression of PKM2 markedly decreased after

we knocked down lncRNA SNHG3 or PKM2 in the C4–2R cells. In

contrast, PKM2 expression was evidently increased after we overexpressed lncRNA SNHG3 or PKM2 in the C4–2 cells (Fig. 3A). Western

blot analysis also confirmed that SNHG3 could positively regulate PKM2

expression in PCa cells (Fig. 3B). We also veriflied the regulation of

PKM2 by SHNG3 in 22RV1 cells. Next, we found that PKM2-

overexpression could reverse the protein expression reduction of

PKM2 resulted from lncRNA SNHG3-knocked down in C4–2R and

22RV1 cells. Similarly, PKM2-knocked down could reverse the protein

expression improvement of PKM2 resulted from lncRNA SNHG3-

overexpression in C4–2 cells. Similar results could be found in 22RV1

cells (Fig. 3C).

Importantly, PKM2 overexpression could reverse sh-lncRNA SNHG3

mediated cell invasion and Enz sensitivity in C4–2R cells (Fig. 3D-E).

Consistently, knockdown of PKM2 could reverse SNHG3 induced cell

invasion and Enz resistance in C4–2 cells (Fig. 3D-E). Similarly, PKM2

knocking-down could reverse the enhancement of cellular invasion and

Enz resistant resulted from lncRNA SNHG3 overexpression in 22RV1

cells.

To confirm the role of lncRNA SNHG3 and PKM2 in vivo, 22RV1 cells

steadily expressing empty vector, sh-lncRNA SNHG3, sh-PKM2, shlncRNA SNHG3 + sh-PKM2 were subcutaneously injected into the flank

areas of nude mice separately. 6 weeks later, tumor weight and tumor

volume of each group were recorded. As exhibited in Fig. 3F, deficiency

of either SNHG3 or PKM2 significantly suppressed tumor growth as

compared to the control cohorts. Of note, simultaneous depletion of

SNHG3 and PKM2 further retarded 22Rv1 tumor growth as compared to

other groups (Fig. 3F).

In conclusion, lncRNA SNHG3 could regulate the PKM2 expression to

promote the development of CRPC.

(caption on next column)

Fig. 1. LncRNA SNHG3 is highly expressed in CRPC and promotes the process

of glycolysis.

(A) PCa-related datasets in TCGA database were used to analyze the expression

level of lncRNA SNHG3 between PCa tissues and normal controls, analyzed

with Student's t-test. P < 0.05 and | fold change | > 1 were considered statistically significant.

(B) The differential analysis of lncRNA SNHG3 gene expression levels between

CSPC tissues and CRPC tissues from dataset GSE35988.

(C) Representative images of FISH with lncRNA SNHG3 probe (in red) and DAPI

(in blue) in normal prostate tissues and PCa tissues (×1000).

(D) Representative images of FISH with lncRNA SNHG3 probe (in red) and

DAPI (in blue) in C4–2 and C4–2R cells (×200).

(E) The mRNA expression of lncRNA SNHG3 in C4–2 and C4–2R cells was

measured by q-PCR.

(F) CCK8 assays were used to detect Enz resistant of C4–2R and C4–2 cells after

lncRNA SNHG3-knocked down.

(G-H) Transwell assays was used to test the invasion abilities of C4–2 cells after

lncRNA SNHG3-overexpression and C4–2R cells after lncRNA SNHG3-knocked

down.

(I) Terms of molecular function with statistical significance were presented in

Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment

analysis.

(J) Glucose uptake determination in C4–2 cells after lncRNA SNHG3-

overexpression and in C4–2R cells after LncRNA SNHG3- knocked down.

(K) Lactate content determination in C4–2 cells after lncRNA SNHG3-

overexpression and in C4–2R cells after lncRNA SNHG3- knocked down.

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3.5. LncRNA SNHG3 can bind to miR-139-5p

Previous reports have proved that miRNA plays an important role as

a ‘bridge’ to connect lncRNA and its targeting mRNA. Therefore, we

sought to screen miRNAs which act as the downstream factor of lncRNA

SNHG3 but the upstream mediator of PKM2 using starBase database (htt

p://starbase.sysu.edu.cn/) (Supplementary Files 2–3). The results

showed that 16 miRNAs were predicated to bind with lncRNA SNHG3

and 18 miRNAs were predicated to guide PKM2 mRNA degradation

(Fig. 4A). Among these miRNAs, three distinct types of miRNAs (miR139-5p, miR-326 and miR-330-5p) were overlapped and selected to the

potential candidates (Fig. 4A). To further confirm whether these three

miRNAs serve as bridges between SNHG3 and PKM2, we first examined

their expression after we knocked down lncRNA SNHG3 in C4–2R cells.

The result demonstrated that only miR-139-5p level was notably

increased by SNHG3 depletion in C4–2R cells (Fig. 4B), suggesting it

may be the bridge connecting SNHG3 and PKM2. Therefore, we presumed that lncRNA SNHG3 might regulate the expression of PKM2

through binding to miR-139-5P competitively, and thus regulated CRPC

development and enzalutamide resistance.

Indeed, the biotin based pull-down assay showed that lncRNA

SNHG3 could bind with miR-139-5p in C4–2 cells (Fig. 4C). More

importantly, the results from qPCR assays revealed that SNHG3 induced

PKM2 mRNA expression was attenuated in the presence of miR-139-5p

in C4–2, C4–2R and 22RV1 cells (Fig. 4D). Similarly, SNHG3 induced

PKM2 protein expression could be reversed by miR-139-5p while shlncRNA SNHG3 mediated PKM2 reduction was blocked by shRNA

against miR-139-5p in C4–2, C4–2R and 22RV1 cells (Fig. 4E-G).

Taking together, we concluded that lncRNA SNHG3 could interact

with miR-139-5p to promote PKM2 expression.

3.6. MiR-139-5p can bind to PKM2

In order to elucidate that how lncRNA SNHG3-regulated miR-139-5p

could affect the PKM2 expression, we identified that there were several

potential miRNA-targeting sites that matched the seed sequence of miR139-5p on the 3′-UTR of PKM2 transcript (Fig. 5B). To confirm the direct

binding, we conducted PKM2 3′-UTR based on luciferase assay, and then

discovered that miR-139-5p could decline the activity of wild type PKM2

3′-UTR rather than mutant PKM2 3′-UTR in C4–2 cells (Fig. 5A), proving

that miR-139-5p could regulate PKM2 expression by binding to its 3′-

UTR. Results from qPCR and Western blot assays corroborated that

knockdown of miR-139-5p increased PKM2 expression in C4–2 cells,

and the overexpression of miR-139-5p reduced PKM2 expression in

(caption on next column)

Fig. 2. PKM2 is highly expressed in CRPC.

(A) Diagram of glycolysis process and main key rate-limiting enzymes.

(B) The heatmap of C4–2 and C4–2R cells metabolites in the 13C –Metabolic

Flux analysis.

(C) The PCA score plot of C4–2 and C4–2R cells metabolites in the 13C

–Metabolic Flux analysis.

(D) The volcano plot of C4–2 and C4–2R cells metabolites in the 13C –Metabolic

Flux analysis.

(E) The OPLS-DA permutation histogram of C4–2 and C4–2R cells metabolites

in the 13C –Metabolic Flux analysis.

(F) The OPLS-DA permutation plot of C4–2 and C4–2R cells metabolites in the

13C –Metabolic Flux analysis.

(G) The protein expression of 4 kinds of typical key rate-limiting enzymes was

measured by western blotting in C4–2 and C4–2R cells.

(H) The protein and RNA expression of PKM2 was measured by western blotting

and qPCR in C4–2, C4–2R and 22RV1 cells.

(I) Representative PKM2 staining divided into Score 1–4 based on staining intensity from weak to strong in PCa tissues.

(J-M) The correlation of PKM2 expression level with Gleason scores (J), T stages

(K), PSA (L) and metastasis (M).

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Fig. 3. LncRNA SNHG3 promotes development of CRPC by regulating the expression of PKM2.

(A) The mRNA expression of PKM2 in C4–2R cells after knocking down lncRNA SNHG3 and PKM2 (upper); The mRNA expression of PKM2 in C4–2 cells after

overexpressing lncRNA SNHG3 and PKM2 (lower).

(B) The protein expression of PKM2 in C4–2R cells after knocking down lncRNA SNHG3 and in C4–2 cells after overexpressing lncRNA SNHG3.

(C) Knocking down lncRNA SNHG3 results in decreasing of PKM2 protein expression, which can be increased by overexpressing PKM2 in C4–2R and 22RV1 cells;

Overexpressing lncRNA SNHG3 results in increasing of PKM2 protein expression, which can be decreased by knocking down PKM2 in C4–2 cells.

(D) Overexpression of PKM2 restored the inhibition effect of Knocking down lncRNA SNHG3 on invasion in C4–2R and 22RV1 cells; Knocking down of PKM2 restored

the promotion effect of Overexpressing lncRNA SNHG3 on invasion in C4–2 cells.

(E) Overexpression of PKM2 restored the inhibition effect of Knocking down lncRNA SNHG3 on Enz resistant in C4–2R and 22RV1 cells; Knocking down of PKM2

restored the promotion effect of Overexpressing lncRNA SNHG3 on Enz resistant in C4–2 cells.

(F) Macroscopic appearance of the tumor xenografts (left); Tumor weight was measured after resection of xenograft tumors (center); Tumor growth curves of 22RV1

cells in nude mice. Values are mean ± SD (n = 5/group) (right).

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Fig. 4. LncRNA SNHG3 can bind to miR-139-5p.

(A) There were 16 downstream miRNAs of lncRNA SNHG3 and 18 upstream miRNAs of PKM2 in the starBase database. Among them there were 3 repeating miRNAs.

(B) The mRNA expression of 3 kinds of miRNAs in C4–2R cells after knocking down lncRNA SNHG3.

(C) The miR-139-5p can physically interact with lncRNA SNHG3.

(D) Overexpression of lncRNA SNHG3 results in increasing of PKM2 mRNA expression, which can be increased by overexpressing miR-139-5p in C4–2 and C4–2R

cells.

(E) Overexpression of lncRNA SNHG3 results in increasing of PKM2 protein expression, which can be decreased by overexpressing miR-139-5p in C4–2 cells.

(F) Knocking down lncRNA SNHG3 results in decreasing of PKM2 protein expression, which can be increased by knocking down miR-139-5p in C4–2R cells.

(G) Knocking down lncRNA SNHG3 results in decreasing of PKM2 protein expression, which can be increased by knocking down miR-139-5p in 22RV1 cells.

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(caption on next page)

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C4–2R and 22RV1 cells (Fig. 5C-D). Meanwhile, miR-139-5p reduced

PKM2 protein expression could be rescued by the introduction of PKM2

in C4–2 and C4–2R cells and sh-miR-139-5p increased PKM2 protein

expression could be blocked by PKM2 shRNAs in C4–2R and 22RV1 cells

(Fig. 5E-G).

In conclusion, miR-139-5p directly interacts with PKM2 and mediates its degradation.

4. Discussion

The anti-androgen drug enzalutamide (Enz) may improve the survival of CRPC patients, but most patients may eventually fail due to the

acquired resistance. There had been substantial evidence that lncRNAs

were inextricably linked to the process of CRPC. Gu et al. [42] found that

lncRNA HOXD-AS1 could regulate proliferation and chemo-resistance of

CRPC via recruiting WDR5. Likewise, Chen et al. [43] determined that

lncRNA LBCS, a novel AR translational regulator, could inhibit the

progression of CRPC. Our study revealed that lncRNA SNHG3/miR-139-

5p/PKM2, a novel mechanism of enzalutamide resistance, may serve as

a molecular basis for clinical treatment of CRPC patients (Fig. 6). Aerobic glycolysis, which is called ‘Warburg effect’, has been suggested as a

new marker for cancer. Targeting cancer cells from the perspective of

glucose metabolism may be an effective therapeutic approaches [10].

PKM2 is a rate-limiting enzyme in the glycolytic pathway, which is

highly expressed in multifarious cancers, including prostate cancer.

Recent studies have shown that lncRNAs and miRNAs can influence

tumor development by regulating PKM2 expression [24–26].

We found lncRNA SNHG3, which has been proven to differ significantly between CSPC and CRPC, as the target gene. Recent studies have

shown that high expression of lncRNA SNHG3 predicts poor prognosis of

PCa patients [44]. Fish assay confirmed that lncRNA SNHG3 expressed

higher in PCa tissues than in para-carcinoma tissues, furthermore

illustrated that lncRNA SNHG3 was mainly distributed in cytoplasm of

C4–2 and C4–2R cells. In previous studies, similar results were found in

another kinds of PCa cells. Wang et al. [45] found that lncRNA SNHG3

was mainly distributed in cytoplasm of LNCaP and Du145 cells. Our

results corroborated that the expression of lncRNA SNHG3 increased

obviously in C4–2R, the Enz-resistant cell lines. Furthermore, the Enz

resistance and invasive abilities of PCa cell lines had distinct positive

correlation with the expression of lncRNA SNHG3. Numerous studies

have shown that overexpression of SNHG3 significantly promotes tumor

migration and invasion [46]. Dai et al. [47] determined that lncRNA

SNHG3 promoted the migratory and invasive ability of bladder cancer

cells through miR-515-5p/GINS2 axis. Zhang et al. [48] found that

Fig. 5. miR-139-5p can bind to PKM2.

(A) Overexpressing miR-139c-5p declined luciferase activity in C4–2 cells transfected with wild-type PKM2 3′ UTR, rather than the mutant PKM2 3′ UTR.

(B) Predicted miR-139-5p target sites in PKM2 3′ UTR.

(C) The mRNA expression of PKM2 in C4–2 cells after knocking down miR-139-5p (left); The mRNA expression of PKM2 in C4–2R cells after overexpressing miR-139-

5p (center); The mRNA expression of PKM2 in 22RV1 cells after overexpressing miR-139-5p (right).

(D) The protein expression of PKM2 in C4–2 cells after knocking down miR-139-5p (left); The protein expression of PKM2 in C4–2R cells after overexpressing miR139-5p (center); The protein expression of PKM2 in 22RV1 cells after overexpressing miR-139-5p (right).

(E) Overexpression of miR-139-5p results in decreasing of PKM2 protein expression, which can be increased by overexpressing PKM2 in C4–2 cells.

(F) Overexpression of miR-139-5p results in decreasing of PKM2 protein expression, which can be increased by overexpressing PKM2 in C4–2R cells.

(G) Overexpression of miR-139-5p results in decreasing of PKM2 protein expression, which can be increased by overexpressing PKM2 in 22RV1 cells.

Fig. 6. Schematic diagram depicting the molecular mechanism of lncRNA SNHG3/miRNA-139-5p/PKM2 axis in CRPC.

LncRNA SNHG3, which is highly expressed in CRPC, can up-regulate the expression of PKM2 by inhibiting miR-139-5p, and promote the degree of Warburg effect

and finally enhance CRPC development and enzalutimade resistance.

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lncRNA SNHG3 promotes clear cell renal cell carcinoma proliferation

and migration by upregulating TOP2A. Therefore, we predicted that

lncRNA SNHG3 acted as an essential oncogene. Then KEGG pathway

enrichment analysis proved that the glycolysis process was the crucial

pathway in the downstream pathways of lncRNA SNHG3. Moreover,

Glucose uptake and Lactate content determination demonstrated that

lncRNA SNHG3 was inextricably linked with the glycolytic pathways.

The 13C –Metabolic Flux analysis showed that the metabolic flux of

glycolysis of C4–2R increased significantly after drug treatment, which

promoted the energy metabolism and the growth of cells. The difference

of PKM2 expression between C4–2 and C4–2R cells was the most significant among 4 kinds of key enzymes. PKM2 has been demonstrated to

overexpressed in various cancers and promoted proliferation of tumor

cells [49]. Wang et al. [50] demonstrated that PKM2 participated in the

pathogenesis of bladder cancer through the HIF-1α/ALYREF/PKM2 axis.

Yu et al. [51] suggested that PKM2 exacerbates the progression of

colorectal cancer by interacting with OTUB2. So we speculate that PKM2

might play a vital role in the progression of PCa as well. Next step, we

verified that PKM2 expression were obviously positively correlated to

lncRNA SNHG3. Then result of the tumor xenograft showed that shlncRNA SNHG3 and sh-PKM2 groups suggested the clear decreased

tumor growth trend compared with the control group.

Previous studies have demonstrated that miRNAs act as a “bridge”

role in linking lncRNAs to their target mRNAs. Wang et al. [52] determined that lncRNA HULC/miR-675/PKM2 pathway accelerated the

growth of human liver cancer stem cells. Lang et al. [53] showed that

lncRNA BCYRN1/miR-149/PKM2 axis promoted tumor progression in

non-small-cell lung cancer. Similarly, we determined that miR-139-5p

played a role of ‘bridge’ in the pathway between lncRNA SNHG3 and

PKM2. Next we confirmed that there were binding sites between lncRNA

SNHG3 and miR-139-5p. There were similar binding sites between miR139-5p and PKM2.

Taken together, our results acknowledged that lncRNA SNHG3 was a

highly expressed gene in CRPC and promoted the process of glycolysis.

PKM2, acted as a kind of key rate-limiting enzyme in glycolysis process,

was highly expressed in PCa. LncRNA SNHG3 could promote the

development of CRPC by regulating the expression of PKM2. And miR139-5p played a role of ‘bridge’ in the pathway between lncRNA

SNHG3 and PKM2. Taking the above results into account, we hypothesized that lncRNA SNHG3 / miRNA-139-5p / PKM2 axis may provide

new perspectives in the treatment of CRPC.

Overall, this study provides a novel mechanism of enzalutamide

resistance, suggesting that targeting the lncRNA SNHG3/miR-139-5p/

PKM2 may serve as a molecular basis for clinical treatment of CRPC

patients. However, further studies are needed to determine the mechanism that PKM2 enhances the Warburg effect to promote CRPC development. Our study has laid a solid foundation for this significant

mechanism.

Supplementary data to this article can be found online at https://doi.

org/10.1016/j.ijbiomac.2024.129635.

Statement of ethics

The Medical Ethics Committee of Shanghai Tongji Hospital examined and approved the studies relating human participants.

Funding

This subject was supported by National Natural Science Foundation

of China (81672526, 81802560), Natural Science Foundation of

Shanghai Municipal Science and Technology Committee (No.

22ZR1456-800) and Key disciplines of Shanghai Tongji Hospital. None

of these study sponsors had any role in study design, collection, analysis,

and interpretation of data.

CRediT authorship contribution statement

Yicong Yao: Formal analysis, Investigation, Methodology, Software,

Validation, Visualization, Writing – original draft. Xi Chen: Data curation, Formal analysis, Visualization. Xin'an Wang: Data curation, Supervision, Validation. Haopeng Li: Investigation. Yaru Zhu:

Investigation. Xilei Li: Investigation. Zhihui Xiao: Investigation. Tong

Zi: Investigation. Xin Qin: Investigation. Yan Zhao: Investigation. Tao

Yang: Investigation. Licheng Wang: Conceptualization, Supervision,

Writing – review & editing. Gang Wu: Conceptualization, Supervision,

Writing – review & editing. Xia Fang: Conceptualization, Methodology,

Writing – review & editing. Denglong Wu: Conceptualization, Funding

acquisition, Methodology, Project administration, Resources, Writing –

review & editing.

Declaration of competing interest

The authors announced that the study was carried out without any

commercial or financial relationships that could be interpreted as a

potential conflict of interest.

Data availability

Data will be made available on request.

Acknowledgments

We were grateful for the investigators and study participants for their

contributions.

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