用于灵敏检测MCF-7细胞的双功能探针及MUC1与多种癌症关联的孟德尔随机化分析-动脉网

Dual-functional probe for sensitive detection of MCF-7 cells and mendelian randomization analysis of MUC1 association with multiple cancers

Nature 等信源发布 2025-02-20 19:22

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可切换为仅中文

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Abstract

摘要

The present study successfully developed a method based on a dual-functional probe for detecting breast cancer cells MCF-7 by recognizing the MUC1 protein on the cell surface. This method integrated inductively coupled plasma mass spectrometry (ICP-MS) and fluorescence imaging technology, enhancing the sensitivity, specificity, and accuracy of breast cancer cell detection.

本研究成功开发了一种基于双功能探针的方法，通过识别细胞表面的MUC1蛋白来检测乳腺癌细胞MCF-7。该方法结合了电感耦合等离子体质谱（ICP-MS）和荧光成像技术，提高了乳腺癌细胞检测的灵敏度、特异性和准确性。

Additionally, through two-sample Mendelian randomization (MR) analysis, we verified a potential correlation between breast cancer and MUC1 (P.

此外，通过两样本孟德尔随机化（MR）分析，我们验证了乳腺癌和MUC1之间存在潜在相关性（P。

IVW

<0.05), while also proving no potential correlation between liver cancer and MUC1 (P

<0.05)，同时证明肝癌与MUC1之间没有潜在相关性（P

IVW

>0.05). Furthermore, this study explored the relationship between other cancers and MUC1, indicating a potential correlation between ovarian cancer and colorectal cancer with MUC1 (P

>0.05）。此外，本研究还探讨了其他癌症与MUC1的关系，结果显示卵巢癌和结直肠癌可能与MUC1存在潜在相关性（P

IVW

<0.05). In summary, this study provides new strategies for the early diagnosis and treatment of breast cancer and offers new insights into the potential of MUC1 as a biomarker for the detection of other cancers.

<0.05）。总之，本研究为乳腺癌的早期诊断和治疗提供了新的策略，并为进一步探索MUC1作为其他癌症检测的生物标志物的潜力提供了新的见解。

Introduction

介绍

Mucin 1 (MUC1) belongs to the mucin family, a large family of highly glycosylated proteins. It is a transmembrane mucin glycoprotein found on the surface of almost all epithelial cells and interacts with invading microorganisms

黏蛋白1（MUC1）属于黏蛋白家族，这是一个高度糖基化蛋白质的大家族。它是一种跨膜黏蛋白糖蛋白，存在于几乎所有上皮细胞的表面，并与侵入的微生物相互作用。

. MUC1 is generally recognized as an important molecule in inflammation and tumor immunity. In cancer cells, the long branches of MUC1’s glycans are truncated, and some short glycans are covered with sialic acid to form tumor-associated carbohydrate antigens (TACAs), which may primarily be due to the overexpression of α 2,6-sialyltransferases and α 2,3-sialyltransferases.

MUC1通常被认为是炎症和肿瘤免疫中的重要分子。在癌细胞中，MUC1的聚糖长分支被截短，一些短聚糖被唾液酸覆盖，形成肿瘤相关碳水化合物抗原（TACAs），这主要可能是由于α2,6-唾液酸转移酶和α2,3-唾液酸转移酶的过表达。

，

. Tumor-associated MUC1 (TA-MUC1) will redistribute on the cell surface and lose polarity

肿瘤相关的MUC1（TA-MUC1）会在细胞表面重新分布并失去极性。

. Abnormal glycosylation and overexpression of MUC1 are common in cancer cells

. 癌细胞中常见的异常糖基化和MUC1过表达

, making it a frequent target for tumor detection markers

，使其成为肿瘤检测标志物的常见靶点

，

。

Breast cancer is one of the most prevalent cancers worldwide

乳腺癌是全球最常见的癌症之一。

. Timely detection of breast cancer is crucial for the progression of the disease. During the process of metastasis, tumor cells undergo an epithelial-to-mesenchymal transition (EMT), enabling them to infiltrate the stroma and enter the circulation as circulating tumor cells (CTCs)

乳腺癌的及时检测对疾病的发展至关重要。在转移过程中，肿瘤细胞经历上皮-间质转化（EMT），使它们能够浸润基质并作为循环肿瘤细胞（CTCs）进入血液循环。

. Therefore, the detection of breast cancer cells is of significant importance. Currently, researchers have developed several MUC1-based methods for its detection. However, the sensitivity of these methods and the issue of false positives still require improvement.

因此，检测乳腺癌细胞具有重要意义。目前，研究人员已经开发了几种基于MUC1的检测方法。然而，这些方法的灵敏度和假阳性问题仍有待改进。

Inductively Coupled Plasma Mass Spectrometry (ICP-MS) is frequently utilized in precision monitoring and analysis due to its high sensitivity, wide linear range, strong resistance to matrix interference, high sample throughput, and robust multi-element analysis capabilities

电感耦合等离子体质谱法 (ICP-MS) 因其高灵敏度、宽线性范围、强抗基质干扰能力、高样品通量和强大的多元素分析能力，常用于精密监测和分析。

. However, the objective of ICP-MS detection is the quantification of metal elements; therefore, it requires the integration of labeling techniques, such as metal nanoparticle tagging, to enable the detection of targets such as proteins, tumor cells, and organic compounds. With the advancement of nanotechnology, a myriad of nanomaterials has been applied across various fields.

然而，ICP-MS检测的目的是金属元素的定量分析，因此需要结合标记技术，如金属纳米颗粒标记，以实现对蛋白质、肿瘤细胞和有机化合物等目标物的检测。随着纳米技术的进步，各种各样的纳米材料已经应用于各个领域。

Gold nanoparticles, known for their antioxidant properties, low toxicity, and stability.

金纳米粒子因其抗氧化特性、低毒性和稳定性而闻名。

, as well as their ability to quench fluorescence

，以及它们淬灭荧光的能力

, are commonly employed in biomedical detection. Carbon dots (CDs), with their tunable emission wavelengths, resistance to photobleaching, good water solubility, and low toxicity, have emerged as one of the most captivating fluorescent materials in recent years

，常用于生物医学检测。碳点（CDs）因其可调的发射波长、抗光漂白性、良好的水溶性和低毒性，近年来成为最引人注目的荧光材料之一。

, and are often used in bioimaging research

，并且常用于生物成像研究中

. Furthermore, nanomaterials are frequently integrated with aptamers for various detection purposes. Aptamers, which are single-stranded oligonucleotides or peptide sequences, exhibit high affinity and specificity, endowing them with significant potential in medical therapy and diagnostics. They can sensitively detect tumor cells based on surface biomarkers.

此外，纳米材料常与适配体结合用于各种检测目的。适配体是单链寡核苷酸或肽序列，具有高亲和力和特异性，这赋予它们在医疗治疗和诊断中的巨大潜力。它们能够基于表面生物标志物灵敏地检测肿瘤细胞。

，

。

Mendelian randomization (MR) is a type of instrumental variable (IV) analysis that employs genetic variants as instrumental variables to investigate the causal relationships between exposures and outcomes

孟德尔随机化（MR）是一种工具变量（IV）分析，它利用遗传变异作为工具变量来研究暴露与结果之间的因果关系。

. Initially, instrumental variable analysis was applied in medicine to address compliance issues in randomized controlled trials (RCTs)

最初，工具变量分析应用于医学领域，以解决随机对照试验（RCT）中的依从性问题。

. However, with the discovery of numerous genetic variants closely associated with specific traits in the biological sciences, coupled with the public release of data from large-scale genome-wide association studies (GWAS)

然而，随着生物学领域中发现大量与特定性状密切相关的遗传变异，并且大规模全基因组关联研究（GWAS）的数据公开发布，

on the relationships between exposures, diseases, and genetic variants, MR has garnered considerable attention from scholars.

基于暴露、疾病和遗传变异之间的关系，MR受到了学者们的广泛关注。

Therefore, this study selected the MCF-7 cell line as a cellular model for breast cancer cells, and liver cancer cells HepG2, which do not overexpress MUC1, along with normal cells BEAS-2B, as control cells. We constructed a dual-functional aptamer sensor based on Au NPs/CDs for the detection of breast cancer cells.

因此，本研究选择MCF-7细胞系作为乳腺癌细胞的细胞模型，选择不过度表达MUC1的肝癌细胞HepG2和正常细胞BEAS-2B作为对照细胞。我们构建了基于金纳米粒子/碳点的双功能适配体传感器，用于检测乳腺癌细胞。

By conjugating the complementary aptamer chain of Au NPs (C.

通过结合金纳米颗粒（Au NPs）的互补适配体链（C.

MCF

-Au NPs) with the recognition aptamer chain attached to magnetic beads (MBs) and CDs (MBs-A

-金纳米粒子（Au NPs）与连接到磁珠（MBs）和CDs上的识别适配体链（MBs-A）

MCF

-CDs), the fluorescence of CDs was quenched. When target cells are present, C

-CDs），CDs的荧光被淬灭。当目标细胞存在时，C

MCF

-Au NPs are displaced into the solution. Subsequently, MBs can be used to magnetically separate the target cells from the supernatant containing C

-金纳米颗粒被释放到溶液中。随后，可以使用MBs磁性分离上清液中的目标细胞。

MCF

-Au NPs. There is a significant difference in the ICP-MS detection results of Au NPs in the supernatant with different numbers of cells, meanwhile, the lower layer sediment can be imaged using an All-in-One fluorescence microscopy imaging system. Based on this, a more sensitive, specific, and accurate detection of breast cancer cells MCF-7 was achieved, and fluorescence imaging of MCF-7 cells was realized through CDs.

-Au NPs。不同数量的细胞上清液中Au NPs的ICP-MS检测结果有显著差异，同时底层沉淀可用All-in-One荧光显微成像系统进行成像。在此基础上，实现了对乳腺癌细胞MCF-7更敏感、特异和准确的检测，并通过CDs实现了对MCF-7细胞的荧光成像。

This approach has the potential for more accurate clinical diagnosis. Furthermore, we utilized two-sample mendelian randomization analysis to explore the relationship between breast cancer and liver cancer with MUC1, as well as the relationship between various cancers and MUC1, to investigate whether MUC1 can serve as a detection marker for other cancers, providing a deeper understanding of the relationship between cancer and MUC1 expression..

这种方法有可能实现更准确的临床诊断。此外，我们利用两样本孟德尔随机化分析来探讨乳腺癌和肝癌与MUC1的关系，以及各种癌症与MUC1的关系，以研究MUC1是否可以作为其他癌症的检测标志物，从而加深对癌症与MUC1表达之间关系的理解。

Materials and methods

材料与方法

Establishment of a method for the detection of breast cancer cells

乳腺癌细胞检测方法的建立

Chemicals and instruments

化学品和仪器

Trisodium citrate (Na

柠檬酸三钠 (Na

·2H

O), hydrochloroauric acid (HAuCl

O)，氯金酸 (HAuCl

·4H

O), hydrochloric acid (HCl), nitric acid (HNO

O）、盐酸（HCl）、硝酸（HNO

), tris (hydroxymethyl) aminomethane (Tris), ethylenediaminetetraacetic acid disodium salt (EDTA), sodium chloride (NaCl) were purchased from Sinopharm Chemical Reagent Co., Ltd. (Shanghai, China). Dynabead™ MyOne™ Streptomycin Affinity C1 was supplied from Thermo Fisher Scientific. (Shanghai, China).

），三（羟甲基）氨基甲烷（Tris）、乙二胺四乙酸二钠盐（EDTA）、氯化钠（NaCl）购自国药集团化学试剂有限公司（中国上海）。Dynabead™ MyOne™ 链霉素亲和C1由赛默飞世尔科技提供（中国上海）。

N-hydroxysuccinimide, albumin from bovine serum (BSA), Tween-20 was obtained from Sigma-Aldrich, (sterile) phosphate buffered saline solution (PBS), RPMI 1640 medium, DMEM medium, foetal bovine serum (FBS), penicillin-streptomycin (double antibody), 0.25% trypsin- EDTA digest was purchased from Hyclone, and all aptamer chains, phosphate buffer salt solution (PBS), and tris(2-carboxyethyl)phosphine (TCEP) were obtained from Sangon Biotech (Shanghai, China) Co.

N-羟基琥珀酰亚胺、牛血清白蛋白（BSA）、Tween-20购自Sigma-Aldrich，（无菌）磷酸盐缓冲液（PBS）、RPMI 1640培养基、DMEM培养基、胎牛血清（FBS）、青霉素-链霉素（双抗）、0.25%胰蛋白酶-EDTA消化液购自Hyclone，所有适配体链、磷酸盐缓冲液（PBS）和三(2-羧乙基)膦（TCEP）均购自上海生工生物工程有限公司。

The aptamer sequences used in this paper were (5’ to 3’): A.

本文使用的适配体序列（5’到3’）为：A。

MCF

: Biotin-TTTTTGCAGTTGATCCTTTGGATACCCTGG-NH

生物素-TTTTTGCAGTTGATCCTTTGGATACCCTGG-NH

, C

，C

MCF

: SH-TTTTTCCAGGGTATCCA. Milli-Q water (18.2 MΩ cm) was used in this work.

：SH-TTTTTCCAGGGTATCCA。本工作中使用了Milli-Q水（18.2 MΩ cm）。

ICP-MS results were mainly obtained from PE NexION 350X (PerkinElmer), TEM results were mainly obtained from FEI Tecnai G2 F20 (FEI, USA), fluorescence imaging was mainly obtained from All-in-One Fluorescence Microscopy Imaging System BZ-X800 (Keens Co. Ltd., China).

ICP-MS结果主要来源于PE NexION 350X（PerkinElmer），TEM结果主要来源于FEI Tecnai G2 F20（FEI，美国），荧光成像主要来源于一体化荧光显微成像系统BZ-X800（基恩有限公司，中国）。

Cells culture

细胞培养

MCF-7 cells were cultured in 25 cm

MCF-7细胞在25平方厘米的条件下培养

cell culture flasks. Cell culture medium were prepared with RPMI medium, 10% (v/v) fetal bovine serum, and 100 U/mL penicillin and streptomycin. Cells were maintained in humidified air at 37 ℃ with 5% CO

细胞培养瓶。细胞培养基使用RPMI培养基、10%（体积比）胎牛血清以及100单位/毫升的青霉素和链霉素配制。细胞在37℃、5%二氧化碳的湿润空气中维持培养。

under standard culture conditions. The medium was changed once a day.

在标准培养条件下，每天更换一次培养基。

HepG2 cells (human hepatocellular carcinoma) and BEAS-2B cells (human normal lung bronchial epithelial cells) were cultured in 25 cm

HepG2细胞（人肝癌细胞）和BEAS-2B细胞（人正常肺支气管上皮细胞）在25平方厘米的培养皿中培养。

cell culture flasks. Cell culture medium were prepared with DMEM medium, 10% (v/v) foetal bovine serum, and 100 U/mL penicillin and streptomycin. Cells were maintained in humidified air at 37 ℃ with 5% CO

细胞培养瓶。细胞培养基采用DMEM培养基、10%（体积比）胎牛血清以及100单位/毫升的青霉素和链霉素配制。细胞在37℃、5%二氧化碳的湿润空气中维持。

under standard culture conditions. The medium was changed once a day.

在标准培养条件下，每天更换一次培养基。

Materials synthesis

材料合成

The gold nanoparticles were synthesised by the trisodium citrate hydrothermal method

通过柠檬酸钠水热法合成了金纳米颗粒。

, 98.3 mL of deionised water and 1.7 mL of chloroauric acid solution (HAuCl

，98.3毫升去离子水和1.7毫升氯金酸溶液（HAuCl）

·6H

O, 2%) were added to a 100 mL two-necked flask, and heated for 140 min, then 10 mL of trisodium citrate (38.8 mM) solution was rapidly injected, and the reaction for 30 min the solution changed to a wine-red colour, which resulted in Au NPs solution, placed in a blue-capped bottle and stored in a refrigerator at 4 ℃ protected from light for use..

将O，2％）加入到100 mL两颈烧瓶中，并加热140分钟，然后迅速注入10 mL柠檬酸三钠（38.8 mM）溶液，反应30分钟后溶液变为酒红色，得到金纳米颗粒溶液，将其放入蓝盖瓶中，避光保存在4℃的冰箱中以备使用。

The CDs were synthesised by microwave method, 0.8 g of trisodium citrate was weighed and finely ground with a mortar, and then placed in a beaker to synthesise CDs by microwave method in a microwave oven. After synthesis, the CDs were re-dissolved in 10 mL of deionised water, and then filtered through 0.22 μm aqueous filtration membranes, and then placed in blue-capped bottles, and then stored in a 4 ℃ refrigerator to protect from light for later use..

通过微波法合成CDs，称取0.8 g柠檬酸三钠并用研钵充分研磨后置于烧杯中，放入微波炉中通过微波法合成CDs。合成后将CDs重新溶解在10 mL去离子水中，然后通过0.22 μm水系滤膜过滤，然后装入蓝盖瓶中，然后置于4 ℃冰箱中避光保存，以备后用。

Conjugate of composite probes

复合探针的共轭物

Conjugate of A

A的共轭

MCF

-CDs: 2.5 µL of CDs was taken and activated by adding NHS (20 mg/mL) and EDC (20 mg/mL) for 60 min at 300 rpm and 37 ℃, then A

-CDs：取2.5 µL CDs，加入NHS（20 mg/mL）和EDC（20 mg/mL），在300 rpm、37℃条件下活化60分钟，然后A

MCF

was added and the reaction was carried out overnight for 12 h.

加入并进行反应，过夜12小时。

Conjugate of MBs- A

MBs-A的共轭

MCF

-CDs: MBs (10 mg/mL) was washed three times with 10 µL of TET buffer and dispersed into 15 µL of TEST buffer, immediately after that, 10 µL of A

-CDs：MBs（10毫克/毫升）用10微升TET缓冲液洗涤三次后，分散到15微升TEST缓冲液中，紧接着加入10微升A

MCF

-CDs was added and the reaction was carried out for 60 min at 37 ℃, 300 rpm. Finally, MBs (10 mg/mL) was washed three times with 10 µL of TET buffer and finally dispersed in 25 µL of TES buffer.

加入CDs后，在37℃、300 rpm条件下反应60分钟。最后，用10 µL TET缓冲液将MBs（10 mg/mL）洗涤三次，并最终分散在25 µL TES缓冲液中。

Conjugate of Au- C

金-碳共轭物

MCF

: 100 µM of TCEP

：100 µM 的 TCEP

was taken and 2.5 µL of C

被取走，并且取了2.5微升的C

MCF

aptamer was added, and the reaction was carried out at room temperature for 60 min. 30 µL of Au NPs was taken and 7.5 µL of C

加入适配体后，在室温下反应60分钟。取30微升金纳米颗粒（Au NPs），并加入7.5微升C

MCF

and 0.72 µL of sodium citrate buffer (pH = 3.0) were added, and the reaction was carried out at room temperature for 10 min. After the reaction was completed, the reaction was centrifuged at 4 ℃ and 12,000 rpm for 10 min and re-dispersed in 25 µL of TES buffer.

加入0.72 µL柠檬酸钠缓冲液（pH = 3.0），在室温下反应10分钟。反应完成后，在4 ℃、12,000 rpm条件下离心10分钟，并重新分散于25 µL TES缓冲液中。

Au- C

金- C

MCF

- MBs- A

MCF

-CDs : 25 µL of each of MBs- A

-CDs：25 µL的每个MBs-A

MCF

-CDs and Au- C

-CDs 和 Au- C

MCF

probes were mixed and reacted at 37 ℃, 400 rpm for 60 min, then washed with 200 µL of TET buffer in an external magnetic field, followed by fixation of 10 µL of PBS. Immediately after that, the reaction was repeated with BSA for 30 min at 37 ℃ and 400 rpm. Immediately after that, the reaction was repeated with BSA at 37 ℃ and 400 rpm for 30 min, and then re-separated and fixed in 10 µL of PBS..

探针混合并在37℃、400 rpm下反应60分钟，然后在外部磁场中用200 µL TET缓冲液洗涤，随后固定于10 µL PBS中。紧接着，在37℃、400 rpm下使用BSA重复反应30分钟。随后，立即再次在37℃、400 rpm下使用BSA重复反应30分钟，然后重新分离并固定于10 µL PBS中。

ICP-MS detection and fluorescence imaging of MCF-7 cells

MCF-7细胞的ICP-MS检测和荧光成像

Digest the cells by centrifugation (500 rpm, 3 min), followed by dilution, then add 10 µL of the composite probe to 200 µL of cell solution and react at 4 ℃ with a rotation speed of 400 rpm for 60 min, after the reaction is complete, use magnetic separation to collect the supernatant, add acid, and pre-digest overnight.

通过离心（500 rpm，3分钟）消化细胞，然后进行稀释，接着将10 µL复合探针加入200 µL细胞溶液中，在4℃下以400 rpm的转速反应60分钟，反应完成后，使用磁分离收集上清液，加酸，并过夜预消化。

The next day, place the sample on a hot plate for heating, after the digestion is complete, dilute to a final volume of 5 mL, and then filter through a membrane filter for ICP-MS analysis. In addition, resuspend the pellet with PBS buffer, transfer to a confocal dish, and perform fluorescence imaging..

第二天，将样品放在热板上加热，消化完成后，稀释至最终体积为5 mL，然后通过膜过滤器过滤以进行ICP-MS分析。此外，用PBS缓冲液重新悬浮沉淀，转移到共聚焦皿中，并进行荧光成像。

Specificity testing

特异性测试

The culture media of 200 µL MCF-7 cells (3000 cells), HepG2 cells (3000 cells), BEAS-2B cells (3000 cells), as well as mixed samples of MCF-7 and HepG2 cells (3000 cells each), MCF-7 and BEAS-2B cells (3000 cells each), and MCF-7, HepG2, and BEAS-2B cells (3000 cells each) were detected using 10 µL of the composite probe.

使用10 µL复合探针检测了200 µL MCF-7细胞（3000个细胞）、HepG2细胞（3000个细胞）、BEAS-2B细胞（3000个细胞），以及MCF-7和HepG2细胞混合样本（各3000个细胞）、MCF-7和BEAS-2B细胞混合样本（各3000个细胞）、MCF-7、HepG2和BEAS-2B细胞混合样本（各3000个细胞）的培养基。

The detection method was consistent with the aforementioned procedure..

检测方法与上述步骤一致。

Actual sample analysis

实际样品分析

To assess the potential application of this method in the analysis of real samples, different quantities of MCF-7 cells were spiked into serum samples for the detection of actual biological specimens. We added 500, 1000, and 3000 MCF-7 cells into the serum and then proceeded with the detection using the proposed method..

为了评估该方法在实际样品分析中的潜在应用，将不同数量的MCF-7细胞掺入血清样品中以检测实际的生物样品。我们向血清中加入了500、1000和3000个MCF-7细胞，然后使用所提出的方法进行检测。

Unless otherwise indicated, all experiments were conducted in triplicate.

除非另有说明，所有实验均重复三次进行。

Mendelian randomization analysis

孟德尔随机化分析

Study design

研究设计

Subsequently, we employed a two-sample Mendelian Randomization (MR) study, utilizing summary data from Genome-Wide Association Studies (GWAS), to explore the causal relationships between breast cancer, liver cancer, and MUC1, as well as between colorectal cancer, ovarian cancer, prostate cancer, gastric cancer, lung cancer, and MUC1 (Supplementary Table 1).

随后，我们采用了两样本孟德尔随机化（MR）研究，利用全基因组关联研究（GWAS）的汇总数据，探讨了乳腺癌、肝癌与MUC1之间，以及结直肠癌、卵巢癌、前列腺癌、胃癌、肺癌与MUC1之间的因果关系（补充表1）。

MR studies should meet three assumptions that the genetic variants must adhere to: (1) a strong correlation with the exposure, (2) independence from confounding factors of both the exposure and the outcome, and (3) an effect on the outcome solely through the exposure.

MR研究应满足遗传变异必须遵循的三个假设：(1) 与暴露因素强烈相关，(2) 独立于暴露和结局的混杂因素，以及 (3) 仅通过暴露对结局产生影响。

. As depicted in Fig.

。如图所示。

, the principle of the two-sample MR analysis is illustrated.

，两样本MR分析的原理如下图所示。

Fig. 1

图1

Overview flowchart of MR analysis assumptions and schematic design.

MR分析假设及示意图设计的总体流程图。

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Data sources and selection

数据来源与选择

In the experimental section, we found a relationship between breast cancer and MUC1, while no relationship was observed between liver cancer and MUC1. Therefore, we selected MUC1 as the outcome measure and breast cancer and liver cancer as exposures to further investigate using the two-sample MR approach.

在实验部分，我们发现了乳腺癌与MUC1之间的关系，而肝癌与MUC1之间未观察到关系。因此，我们选择MUC1作为结果指标，乳腺癌和肝癌作为暴露因素，使用两样本MR方法进一步研究。

Additionally, this study selected other types of cancer as exposure measures to explore their relationship with MUC1, including colorectal cancer, ovarian cancer, prostate cancer, gastric cancer, and lung cancer. The MR summary data mainly come from the Genome-Wide Association Studies catalog (.

此外，本研究还选择了其他类型的癌症作为暴露指标，以探索它们与MUC1的关系，包括结直肠癌、卵巢癌、前列腺癌、胃癌和肺癌。MR汇总数据主要来源于全基因组关联研究目录（GWAS）。

https://gwas.mrcieu.ac.uk/

), with the study population primarily consisting of individuals of European descent. Supplementary Table 2 provides detailed information on the GWAS summary databases used in this study.

)，研究人群主要由欧洲裔个体组成。补充表2提供了本研究中使用的GWAS汇总数据库的详细信息。

During the data extraction process, we extracted single nucleotide polymorphisms (SNPs) corresponding to the study factors in the GWAS data with a p-value less than 5 × 10^-8 as instrumental variables and removed SNPs in linkage disequilibrium, with the critical threshold parameters set to r

在数据提取过程中，我们提取了与GWAS数据中研究因素对应的单核苷酸多态性（SNPs），其p值小于5×10^-8作为工具变量，并去除了连锁不平衡的SNPs，关键阈值参数设定为r。

≤ 0.001 and kb ≤ 10,000. Supplementary Table 3 lists the F-statistics for these SNPs, all of which are greater than 10 to ensure the exclusion of weak instrumental variables, thereby confirming a strong correlation between the instrumental variables and all exposure measures and the robustness of the instrumental variables..

≤ 0.001 且 kb ≤ 10,000。补充表 3 列出了这些 SNP 的 F 统计量，所有统计量均大于 10，以确保排除弱工具变量，从而确认工具变量与所有暴露测量之间的强相关性以及工具变量的稳健性。

Statistical analysis

统计分析

The MR Egger regression method takes into account the potential heterogeneity of variables and provides an adjusted estimate of the causal effect. The slope obtained from this method represents the estimated causal effect

MR Egger回归方法考虑了变量的潜在异质性，并提供了因果效应的调整估计值。通过该方法获得的斜率代表了估计的因果效应。

. The median method requires that at least half of the genetic instruments used in the summary data are effective to achieve a consistent effect size. This includes the simple median method, the weighted median method, and the penalized weighted median estimation. Among these, the weighted median method combines the weighted estimation and the median, allowing for an accurate assessment of the causal effect of each genetic variant based on different weights.

中位数方法要求汇总数据中使用的遗传工具至少有一半是有效的，才能获得一致的效应大小。这包括简单中位数法、加权中位数法和惩罚加权中位数估计。其中，加权中位数法结合了加权估计和中位数，能够根据不同权重准确评估每个遗传变异的因果效应。

，

. The inverse-variance weighting (IVW) method is the standard approach for summarizing MR data, which can directly estimate the causal relationship between study subjects using summary data

逆方差加权（IVW）方法是汇总MR数据的标准方法，可以使用汇总数据直接估计研究对象之间的因果关系。

. The leave-one-out method involves identifying SNP sites that may influence the MR results, sequentially removing SNP sites that do not conform, thereby reducing the impact of a specific SNP site on the outcome. To correct for multiple testing, Bonferroni-corrected p-values were applied, with

留一法涉及识别可能影响MR结果的SNP位点，依次剔除不符合的SNP位点，从而减少特定SNP位点对结果的影响。为了校正多重检验，应用了Bonferroni校正的p值，

= 0.05/8 = 0.00625 in this study. Statistical analyses were conducted using R software (version 4.3.2) and the R package (TwoSample MR).

= 0.05/8 = 0.00625 在本研究中。统计分析使用 R 软件（版本 4.3.2）和 R 包（TwoSample MR）进行。

Results

结果

Establishment of MCF-7 cell detection method

建立MCF-7细胞检测方法

Development of a detection method for MCF-7 cells using ICP-MS combined with composite probes

使用ICP-MS结合复合探针检测MCF-7细胞的方法开发

As illustrated in Fig.

如图所示。

, to achieve the detection and fluorescence imaging of MCF-7 cells, we conjugated CDs with the aptamer A

，为了实现对MCF-7细胞的检测和荧光成像，我们将CDs与适配体A结合

MCF

through an amide bond coupling. Subsequently, these were combined with the complementary aptamer C

通过酰胺键耦合。随后，这些与互补适配体C结合

MCF

attached to Au nanoparticles (Au NPs) and the aptamer conjugated with CDs, effectively quenching the fluorescence of CDs via the FRET (Forster Resonance Energy Transfer) effect of Au NPs. In the presence of target cells, the binding affinity of the A

附着在金纳米颗粒（Au NPs）上，并与CDs结合的适配体，通过Au NPs的FRET（福斯特共振能量转移）效应有效淬灭CDs的荧光。在目标细胞存在的情况下，A的结合亲和力

MCF

aptamer for MUC1 on the surface of MCF-7 cells is stronger than its affinity for C

MUC1在MCF-7细胞表面的适配体对其亲和力强于对C的亲和力

MCF

, leading to the release of C

，导致C的释放

MCF

-Au NPs into the solution and the restoration of CDs fluorescence. After magnetic separation, the supernatant containing C

-将Au NPs加入溶液中，并恢复CDs的荧光。磁分离后，含有C的上清液

MCF

-Au NPs was used for ICP-MS detection, while the pellet containing CDs was used for fluorescence imaging. In contrast, when target cells are absent, the FRET effect of Au NPs keeps the CDs fluorescence quenched, and Au NPs cannot be detected in the supernatant. Finally, ICP-MS is used for quantitative detection of Au NPs in the supernatant, and an All-in-One fluorescence microscopy imaging system is employed for fluorescence imaging of the MCF-7 cells in the pellet..

- Au NPs 用于 ICP-MS 检测，而含有 CDs 的沉淀用于荧光成像。相反，当目标细胞不存在时，Au NPs 的 FRET 效应使 CDs 的荧光保持淬灭，并且 Au NPs 无法在上清液中被检测到。最后，ICP-MS 用于定量检测上清液中的 Au NPs，而一体化荧光显微成像系统则用于对沉淀中的 MCF-7 细胞进行荧光成像。

Fig. 2

图2

Schematic diagram of the synthesis of the composite probe and the principle of ICP-MS detection and fluorescence imaging of MCF-7.

复合探针合成示意图及ICP-MS检测和MCF-7荧光成像原理。

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Characterization of au NPs and CDs

金纳米颗粒和碳点的表征

In Fig.

图中。

A,B, we present the transmission electron microscopy (TEM) images of gold nanoparticles (Au NPs) along with their corresponding Gaussian size distribution plots. From the TEM image in Fig.

A,B，我们展示了金纳米颗粒（Au NPs）的透射电子显微镜（TEM）图像及其相应的高斯尺寸分布图。从图中的TEM图像可以看出。

A, it can be clearly observed that the Au NPs exhibit a regular spherical shape. This uniform distribution indicates precise control over particle size and morphology during the synthesis process. Furthermore, we conducted a statistical analysis of the size distribution of the Au NPs, which is depicted in the form of a Gaussian distribution plot in Fig. .

A，可以清楚地观察到Au纳米颗粒呈现出规则的球形。这种均匀的分布表明在合成过程中对颗粒尺寸和形态进行了精确控制。此外，我们对Au纳米颗粒的尺寸分布进行了统计分析，其结果以高斯分布图的形式展示在图中。

B. In summary, we have synthesized Au NPs that are regular in shape and uniform in size, with a particle diameter of 13.48 nm.

B. 总之，我们已经合成了形状规则、尺寸均匀、粒径为13.48纳米的金纳米颗粒。

Fig. 3

图3

TEM (

透射电子显微镜 (

) and particle size distribution (

）和粒度分布（

) of Au NPs, Transmission electron micrograph (

) 的金纳米颗粒，透射电子显微照片 (

) and particle size distribution (

）和粒度分布（

) of CDs.

）的CD。

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In Fig.

图中。

C,D, we display the TEM images of CDs along with their corresponding Gaussian size distribution plots. From the TEM image in Fig.

C,D，我们展示了CDs的TEM图像及其对应的高斯尺寸分布图。从图中的TEM图像可以看出。

C, it is evident that the CDs exhibit a circular shape, indicating precise control over the shape of the CDs during the synthesis process. Subsequently, we conducted a detailed analysis of the size distribution of the CDs, which is presented in the form of a Gaussian distribution plot in Fig.

C，显然CDs呈现圆形，表明在合成过程中对CDs的形状进行了精确控制。随后，我们对CDs的尺寸分布进行了详细分析，结果以高斯分布图的形式呈现在图中。

D. By fitting the Gaussian distribution curve and in conjunction with the TEM images, we determined that the synthesized CDs have a particle diameter of 6.25 nm.

D. 通过拟合高斯分布曲线并结合TEM图像，我们确定合成的CDs的粒径为6.25 nm。

As depicted in Fig.

如图所示。

, the spectral properties of hydrothermally synthesized CDs were characterized, encompassing ultraviolet-visible (UV-Vis) absorption spectroscopy, excitation spectroscopy, and emission spectroscopy. The UV-Vis absorption spectrum indicates a distinct absorption peak at 321 nm for the CDs. The black and red lines in the figure represent the excitation and emission spectra of the CDs, respectively.

通过水热合成的CDs的光谱特性进行了表征，包括紫外-可见（UV-Vis）吸收光谱、激发光谱和发射光谱。UV-Vis吸收光谱表明CDs在321 nm处有一个明显的吸收峰。图中的黑线和红线分别代表CDs的激发光谱和发射光谱。

It is observable from the figure that the fluorescence emission intensity of the CDs is maximized at an excitation wavelength of 390 nm, with an emission peak at 484 nm. The aforementioned results suggest that the CDs possess excellent optical properties..

从图中可以观察到，CDs的荧光发射强度在激发波长为390 nm时达到最大，发射峰位于484 nm。上述结果表明CDs具有优良的光学性能。

Fig. 4

图4

UV-vis absorption and fluorescence spectra of CDs.

CDs的紫外-可见吸收光谱和荧光光谱。

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Figure

图

A presents the ultraviolet-visible (UV-Vis) absorption spectra of gold nanoparticles (Au NPs) before and after surface modification with DNA. UV-Vis absorption spectroscopy is a commonly utilized spectroscopic method for analyzing the optical properties of nanomaterials and their surface modification status.

A展示了金纳米粒子（Au NPs）在DNA表面修饰前后的紫外-可见（UV-Vis）吸收光谱。紫外-可见吸收光谱是一种常用于分析纳米材料光学性质及其表面修饰状态的光谱方法。

In this study, we compared the spectral changes before and after modification to confirm the successful surface modification of Au NPs with DNA. In the absence of DNA modification, the UV-Vis absorption spectrum of Au NPs exhibited a characteristic absorption peak at 520 nm. This peak is typically associated with the surface plasmon resonance (SPR) effect of Au NPs, which is one of the unique optical properties of gold nanoparticles.

在本研究中，我们比较了修饰前后的光谱变化，以确认 Au NPs 通过 DNA 进行表面修饰的成功。在没有 DNA 修饰的情况下，Au NPs 的紫外-可见吸收光谱在 520 nm 处表现出特征吸收峰。该峰通常与 Au NPs 的表面等离子体共振 (SPR) 效应相关，这是金纳米粒子独特的光学特性之一。

The SPR effect leads to strong absorption and scattering of Au NPs at specific wavelengths. After the surface modification of Au NPs with DNA, the peak position in the UV-Vis absorption spectrum shifted to 524 nm. This redshift (i.e., an increase in wavelength) is an important indicator of successful DNA modification.

SPR效应导致金纳米粒子（Au NPs）在特定波长下产生强烈的吸收和散射。通过DNA对金纳米粒子进行表面修饰后，紫外-可见吸收光谱中的峰值位置移动至524 nm。这种红移（即波长增加）是DNA修饰成功的的重要标志。

The redshift in the peak position may be due to changes in the local refractive index caused by the interaction between the DNA molecules and the surface of Au NPs, or it may be due to the coupling effect between the electronic structure of the DNA molecules and the SPR mode of the Au NPs. The results confirm that DNA has been modified on the surface of Au NPs, forming a stable Au NPs-DNA complex.

峰值位置的红移可能是由于DNA分子与Au NPs表面相互作用引起的局部折射率变化，或者是由于DNA分子的电子结构与Au NPs的SPR模式之间的耦合效应。结果证实DNA已修饰在Au NPs表面，形成了稳定的Au NPs-DNA复合物。

The findings are consistent with the results reported by Li et al..

研究结果与李等人报告的结果一致。

Furthermore, we conducted Dynamic Light Scattering (DLS) measurements on Au NPs before and after DNA modification to further substantiate that DNA has been successfully conjugated onto the surface of the Au NPs. The DLS results demonstrated a shift in the hydrodynamic diameter, which served as evidence for the successful attachment of DNA to the Au NPs, as shown in Fig. .

此外，我们对DNA修饰前后的Au NPs进行了动态光散射（DLS）测量，以进一步证实DNA已成功结合到Au NPs表面。DLS结果显示水动力学直径发生了变化，这作为DNA成功附着在Au NPs上的证据，如图所示。

B. The hydrodynamic size was 13.5 nm before DNA modification, and increased to 15.7 nm after DNA immobilization, indicating that DNA was indeed conjugated onto the surface of Au NPs.

B. DNA修饰前的水动力学尺寸为13.5 nm，在DNA固定后增加到15.7 nm，这表明DNA确实结合到了金纳米粒子的表面。

Fig. 5

图5

UV patterns (

紫外线图案 (

) and DLS (

）和DLS（

) of DNA before and after Au modification.

）的DNA在Au修饰前后的变化。

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Feasibility analysis

可行性分析

As shown in Fig.

如图所示。

, There were differences between the blank and the sample groups. In the sample group, we added 3000 MCF-7 cells, while in the blank group, we added an equal volume of culture medium; all other conditions were kept consistent. In the presence of MCF-7 cells, the Au NPs on the composite probe were released into the solution and thus became detectable in the solution.

空白组与样本组之间存在差异。在样本组中，我们加入了3000个MCF-7细胞，而在空白组中，我们加入了等量的培养基，其他所有条件保持一致。在MCF-7细胞的存在下，复合探针上的金纳米颗粒被释放到溶液中，从而在溶液中可被检测到。

The detection results indicated that the CPS (Counts Per Second) response value of the sample group was approximately four times that of the blank group, demonstrating the feasibility of the proposed method and the ability of the synthesized composite probe to detect MCF-7 cells..

检测结果显示，样品组的CPS（每秒计数）响应值约为空白组的四倍，证明了所提出方法的可行性以及合成的复合探针检测MCF-7细胞的能力。

Fig. 6

图6

Feasibility analysis.

可行性分析。

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Optimization of experimental conditions

实验条件的优化

To achieve a detection method with better performance, we optimized the conditions of the entire system, which mainly included the concentration of A

为了实现性能更好的检测方法，我们优化了整个系统的条件，主要包括A的浓度。

MCF

, the ratio between A

，A之间的比率

MCF

and its complementary strand C

及其互补链 C

MCF

, the concentration of Au, and the reaction time.

，金的浓度，以及反应时间。

The concentration of aptamer DNA strands plays a significant role in the recognition and capture of MCF-7 cells. At the same time, the concentration of aptamer strands immobilized on the surface of magnetic beads (MBs) may influence the detection effect. To facilitate more effective binding of the recognition aptamer strands to the target cells, we optimized the concentration of the aptamer A.

适配体DNA链的浓度在MCF-7细胞的识别和捕获中起着重要作用。同时，固定在磁珠（MBs）表面的适配体链浓度可能影响检测效果。为了促进识别适配体链与目标细胞更有效的结合，我们优化了适配体A的浓度。

MCF

within the range of 0.4 µM to 0.9 µM using 5,000 cells as the detection subject. As shown in Fig.

在0.4 µM至0.9 µM的范围内，使用5,000个细胞作为检测对象。如图所示。

A, the CPS value of Au NPs reaches its maximum at a concentration of 0.6 µM. Within the range of 0.4 µM to 0.6 µM, the CPS value shows an upward trend, whereas within the range of 0.6 µM to 0.9 µM, the CPS value shows a downward trend. Therefore, for the entire reaction system, the optimal concentration of A.

A，Au NPs的CPS值在浓度为0.6 µM时达到最大。在0.4 µM到0.6 µM范围内，CPS值呈上升趋势，而在0.6 µM到0.9 µM范围内，CPS值呈下降趋势。因此，对于整个反应体系，A的最佳浓度为0.6 µM。

MCF

is determined to be 0.6 µM.

被确定为0.6 µM。

The stoichiometric ratio of the two complementary aptamers, A

两种互补适配体的化学计量比，A

MCF

and C

和 C

MCF

, may influence the experimental outcomes. Therefore, we optimized the ratio of the aptamer A

，可能影响实验结果。因此，我们优化了适配体A的比例

MCF

to its complementary strand C

与其互补链C

MCF

. The results are depicted in Fig.

。结果如图所示。

B, where the optimization was conducted over a range of ratios from 1:1 to 1:3.5 (A

B，优化是在从1:1到1:3.5的比例范围内进行的（A

MCF

: C

：C

MCF

). An upward trend was observed within the range of 1:1 to 1:2, while a downward trend was noted in the range from 1:2 to 1:3.5. Consequently, for the entire reaction system, the optimal ratio is determined to be 1:2.

). 在1:1到1:2的范围内观察到上升趋势，而在1:2到1:3.5的范围内则出现下降趋势。因此，对于整个反应体系，最佳比例确定为1:2。

If the Au NPs are modified in insufficient quantities, it may lead to a relatively low CPS (Counts Per Second) response value in the presence of target cells. Conversely, when modified in excess, the strong binding affinity between Au NPs and MBs might prevent the Au NPs from being effectively separated into the solution.

如果Au NPs修饰量不足，可能会导致在目标细胞存在下CPS（每秒计数）响应值相对较低。相反，当修饰过量时，Au NPs与MBs之间的强结合亲和力可能会阻止Au NPs有效分离到溶液中。

Therefore, we proceeded to optimize the concentration of Au. The results are presented in Fig. .

因此，我们继续优化了金的浓度。结果如图所示。

C where the optimization was carried out within the range of 1 µg/mL to 5 µg/mL. Upon reaching a concentration of 3 µg/mL, the CPS response value entered a plateau phase. Consequently, the most suitable concentration of Au is determined to be 3 µg/mL.

在1 µg/mL至5 µg/mL的范围内进行了优化。当浓度达到3 µg/mL时，CPS响应值进入平台期。因此，确定Au的最适浓度为3 µg/mL。

Lastly, to ensure adequate interaction between the constructed probe and the target cells, allowing for sufficient release of Au NPs, we also optimized the reaction time. As shown in Fig.

最后，为了确保构建的探针与目标细胞之间有足够的相互作用，从而充分释放金纳米粒子，我们还优化了反应时间。如图所示。

D, the optimization was conducted over a range of 10 to 180 min. The response value was in an ascending phase up to 60 min, after which it began to decline. Therefore, the optimal reaction time is determined to be 60 min.

D，在10到180分钟的范围内进行了优化。响应值在60分钟之前处于上升阶段，之后开始下降。因此，确定最佳反应时间为60分钟。

Fig. 7

图7

Optimization of bMCF-7 concentration (

bMCF-7浓度的优化（

), optimization of bMCF-7 to C

)，优化bMCF-7到C

MCF

ratio (

比率（

), optimization of Au concentration (

），优化Au浓度（

) and optimization of reaction time(D).

）以及反应时间（D）的优化。

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Specificity analysis

特异性分析

As depicted in Fig.

如图所示。

A, we conducted detection on 200 µL culture media containing MCF-7 cells (3,000), HepG2 cells (3,000), BEAS-2B cells (3,000), as well as mixtures of MCF-7 and HepG2 cells (3,000 each), MCF-7 and BEAS-2B cells (3,000 each), and a combination of MCF-7, HepG2, and BEAS-2B cells (3,000 each) to investigate the specificity of the synthesized composite probe for detecting MCF-7 cells.

A，我们对含有MCF-7细胞（3,000个）、HepG2细胞（3,000个）、BEAS-2B细胞（3,000个）以及MCF-7和HepG2细胞混合物（各3,000个）、MCF-7和BEAS-2B细胞混合物（各3,000个），以及MCF-7、HepG2和BEAS-2B细胞组合（各3,000个）的200 µL培养基进行了检测，以研究合成的复合探针对MCF-7细胞检测的特异性。

The results presented in Fig. .

图中展示的结果。

A indicate that the synthesized probe exhibits relatively good selectivity and sensitivity for MCF-7 cells. Compared to the groups without MCF-7, the CPS values in the groups containing MCF-7 were significantly elevated. The CPS response values for groups containing only HepG2 and BEAS-2B cells were not significantly different from those of the blank group, while the detection results for groups containing MCF-7 cells were similar.

A表明合成的探针对MCF-7细胞具有相对良好的选择性和灵敏度。与不含MCF-7的组相比，含有MCF-7的组CPS值显著升高。仅含HepG2和BEAS-2B细胞的组其CPS响应值与空白组无显著差异，而含MCF-7细胞的组检测结果相似。

Additionally, the results from the E-G group demonstrated that the presence of HepG2 and BEAS-2B cells does not interfere with the detection of MCF-7 cells by this method. Collectively, these results suggest that our composite probe has good specificity for MCF-7 cells, capable of specifically recognizing MCF-7 cells..

此外，E-G组的结果表明，HepG2和BEAS-2B细胞的存在不会干扰该方法对MCF-7细胞的检测。总体而言，这些结果表明我们的复合探针对于MCF-7细胞具有良好的特异性，能够特异性识别MCF-7细胞。

Furthermore, to assess the reproducibility of the method we have developed, we performed 5 different batches of assays with the same cell number, and each group also performed 3 measurements, and the RSD between the 5 sets of assays = 3.93% (Fig.

此外，为了评估我们所开发方法的可重复性，我们用相同的细胞数量进行了5个不同批次的测定，每组也进行了3次测量，5组测定之间的RSD = 3.93%（图。

B), indicating that the experimental results of the method we constructed were reproducible.

B)，表明我们构建的方法的实验结果是可重复的。

Fig. 8

图8

Specificity and cross-reaction tests (

特异性和交叉反应测试 (

) for MCF-7 cells(a: Blank b: 3,000 MCF-7 cells c: 3,000 HepG2 cells d: 3,000 BEAS-2B e: 3,000 MCF-7 cells and 3,000 HepG2 cells f:3,000 MCF-7 cells and 3,000 BEAS-2B cells g: 3,000 MCF-7 cells and 3,000 HepG2 cells and 3,000 BEAS-2B cells) and reproducibility of the method (

) 对于MCF-7细胞(a: 空白 b: 3,000个MCF-7细胞 c: 3,000个HepG2细胞 d: 3,000个BEAS-2B细胞 e: 3,000个MCF-7细胞和3,000个HepG2细胞 f: 3,000个MCF-7细胞和3,000个BEAS-2B细胞 g: 3,000个MCF-7细胞、3,000个HepG2细胞和3,000个BEAS-2B细胞) 以及方法的可重复性 (

), RSD = 3.93%.

），RSD = 3.93%。

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Fluorescence imaging

荧光成像

Following the successful demonstration of the high specificity and quantitative capability of our established method in the analysis of MCF-7 cells, we further explored the probe’s capability in fluorescence imaging. Fluorescence imaging of cells can serve as a complement to ICP-MS, further excluding false negatives and false positives at the imaging level.

在成功展示我们建立的方法在MCF-7细胞分析中的高特异性和定量能力后，我们进一步探索了该探针在荧光成像中的能力。细胞荧光成像可以作为ICP-MS的补充，在成像层面进一步排除假阴性和假阳性。

As shown in Fig. .

如图所示。

, we used hepatocellular carcinoma cells (HepG2) as control cells and applied our synthesized composite probe for fluorescence imaging of target cells, MCF-7, and HepG2. The images from left to right are fluorescence field, bright field, and the composite field. When MCF-7 cells are present, the composite probe specifically binds to the surface of MCF-7 cells, and the Au NPs that play a role in fluorescence quenching are displaced into the solution.

，我们使用肝癌细胞（HepG2）作为对照细胞，并应用我们合成的复合探针进行靶细胞MCF-7和HepG2的荧光成像。从左到右的图像分别是荧光场、明场和复合场。当存在MCF-7细胞时，复合探针特异性结合到MCF-7细胞表面，起到荧光淬灭作用的金纳米颗粒被置换到溶液中。

Therefore, under an inverted fluorescence microscope, the fluorescence imaging results of CDs on the surface of MCF-7 cells can be observed. At the same time, in the bright field, it is clear to see that magnetic beads are adsorbed on the surface of MCF-7 cells. In the absence of MCF-7 cells, only negligible fluorescence is observed on the cell surface, and under the bright field conditions, it is evident that not many magnetic beads are adsorbed.

因此，在倒置荧光显微镜下，可以观察到CDs在MCF-7细胞表面的荧光成像结果。同时，在明场中，可以清楚地看到磁珠吸附在MCF-7细胞表面。在没有MCF-7细胞的情况下，细胞表面仅观察到可忽略的荧光，并且在明场条件下，明显吸附的磁珠不多。

The results indicate that our composite probe can achieve fluorescence imaging, providing intuitive images for the analysis of breast cancer cells..

结果表明，我们的复合探针可以实现荧光成像，为乳腺癌细胞的分析提供直观的图像。

Fig. 9

图9

Fluorescence imaging of MCF-7 cells and HepG2 cells incubated with composite probes, respectively.

分别与复合探针孵育的MCF-7细胞和HepG2细胞的荧光成像。

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Evaluation of analytical performance

分析性能评估

As depicted in Fig.

如图所示。

, to more comprehensively assess the sensitivity of the MCF-7 cell detection based on the composite probe combined with ICP-MS, we conducted detection with varying numbers of MCF-7 cells. With the increase in the number of cells, the response value of ICP-MS also gradually increased. A linear fit yielded the linear equation: y = 1.526x − 273.75 (y: ICP-MS response value, x: number of cells), with a correlation coefficient R.

，为了更全面地评估基于复合探针结合ICP-MS的MCF-7细胞检测的灵敏度，我们进行了不同数量MCF-7细胞的检测。随着细胞数量的增加，ICP-MS的响应值也逐渐升高。线性拟合得到线性方程：y = 1.526x − 273.75（y：ICP-MS响应值，x：细胞数量），相关系数为R。

= 0.9951. The results indicate that within the range of 500 to 7000 MCF-7 cells, the ICP-MS detection results exhibit a good linear relationship. Moreover, the LOD for this method was calculated by 3σ/k to be 98 cells, where σis the standard deviation of the CPS values of the blank samples and k is the slope of the correlation equation.

= 0.9951。结果表明，在500至7000个MCF-7细胞范围内，ICP-MS检测结果呈现出良好的线性关系。此外，该方法的检出限（LOD）通过3σ/k计算为98个细胞，其中σ为空白样品CPS值的标准偏差，k为相关方程的斜率。

Table .

表格。

presents a comparison of this method with other reported methods for detecting circulating tumor cells in the literature. It can be observed that the detection limit of this method is comparable to most ICP-MS-based methods and is lower than methods such as fluorescence detection.

展示了该方法与文献中其他报道的循环肿瘤细胞检测方法的比较。可以看出，该方法的检测限与大多数基于ICP-MS的方法相当，并且低于荧光检测等方法。

Fig. 10

图10

Au CPS response values versus MCF-7 cell concentration. 500, 1000, 2000, 3000, 5000, and 7000 MCF-7 cells from left to right, respectively.

CPS响应值与MCF-7细胞浓度的关系。从左到右分别为500、1000、2000、3000、5000和7000个MCF-7细胞。

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Table 1 Comparison of the performance of various methods for detecting CTCs.

表1 各种CTC检测方法性能比较。

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Recovery test

恢复测试

To evaluate the potential application of this method in the analysis of real samples, we conducted spiked recovery experiments by adding different quantities of MCF-7 cells to serum. As shown in Table

为了评估该方法在实际样品分析中的潜在应用，我们通过向血清中添加不同数量的MCF-7细胞进行了加标回收实验。如表所示

, the results indicate that the recovery rates of human blood MCF-7 cells at four concentration levels ranged from 89.2 to 117.3%. These results demonstrate that the dual-functional aptamer sensor based on nanogold/CDs, which we have constructed, can be utilized for the detection of breast cancer cells MCF-7..

结果表明，人血中MCF-7细胞在四个浓度水平下的回收率范围为89.2%至117.3%。这些结果证明，我们构建的基于纳米金/碳点的双功能适配体传感器可以用于检测乳腺癌细胞MCF-7。

Table 2 Recovery test (

表2 回收试验 (

= 3).

= 3)。

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MR analysis results

MR分析结果

Instrumental variable situation

工具变量情形

The instrumental variables extracted from the relevant GWAS summary data are as follows: 136 SNPs are associated with breast cancer, 12 SNPs are associated with colorectal cancer, 71 SNPs are associated with ovarian cancer, 4 SNPs are associated with liver cancer, 34 SNPs are associated with prostate cancer, 8 SNPs are associated with gastric cancer, 12 SNPs are associated with lung cancer..

从相关的GWAS汇总数据中提取的工具变量如下：136个SNP与乳腺癌相关，12个SNP与结直肠癌相关，71个SNP与卵巢癌相关，4个SNP与肝癌相关，34个SNP与前列腺癌相关，8个SNP与胃癌相关，12个SNP与肺癌相关。

Two-Sample Mendelian Randomization of Multiple Cancers with MUC1.

多种癌症与MUC1的两样本孟德尔随机化研究。

We employed a two-sample MR study method to explore the causal relationships between multiple cancers and MUC1. In the IVW analysis, breast cancer was found to be negatively correlated with MUC1 expression, while colorectal cancer and ovarian cancer showed a positive correlation with MUC1 expression, in the analysis of other cancers, the IVW results were not statistically significant (P.

我们采用两样本MR研究方法来探索多种癌症与MUC1之间的因果关系。在IVW分析中，发现乳腺癌与MUC1表达呈负相关，而结直肠癌和卵巢癌与MUC1表达呈正相关，在其他癌症的分析中，IVW结果未达到统计学显著性（P）。

IVW

> 0.05). The specific results are shown in Figs.

> 0.05）。具体结果如图所示。

and

和

, with Fig.

，如图所示。

illustrating the relationship between breast cancer and liver cancer with MUC1, and Fig.

用MUC1说明乳腺癌和肝癌之间的关系，以及图。

showing the relationships between other cancers and MUC1. Scatter plots provide the estimates of MUC1 for each SNP site corresponding to various cancers, as depicted in Fig.

显示了其他癌症与MUC1之间的关系。散点图提供了对应于各种癌症的每个SNP位点的MUC1估计值，如图所示。

. Supplementary Table 4 reveals that Cochrane Q-tests indicated no significant heterogeneity between the investigated seven cancers and MUC1 (P

补充表4显示，Cochrane Q检验表明所研究的七种癌症与MUC1之间不存在显著的异质性（P

Cochrane Q

科克伦Q

> 0.05).

> 0.05)。

Fig. 11

图11

MR analysis of breast and liver cancer to MUC1 in the the European population.

对欧洲人群中乳腺癌和肝癌与MUC1的MR分析。

或

odds ratio,

比值比，

持续集成

confidence interval,

置信区间，

磁共振成像

mendelian randomization.

孟德尔随机化。

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Fig. 12

图12

MR analysis of colorectal, ovarian, prostate, gastric and lung cancer to MUC1 in the the European population.

对欧洲人群中结直肠癌、卵巢癌、前列腺癌、胃癌和肺癌与MUC1的MR分析。

或者

odds ratio,

比值比，

持续集成

confidence interval,

置信区间，

磁共振成像

mendelian randomization.

孟德尔随机化。

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Fig. 13

图13

Scatter plot of SNPs associated with multiple cancers on MUC1. (

与多种癌症相关的MUC1上的SNPs散点图。(

) breast cancer on MUC1; (

`) 乳腺癌与MUC1相关； (`

) liver cancer on MUC1; (

) 肝癌与MUC1的关系；(

C语言

) colorectal cancer on MUC1; (

) 结直肠癌与MUC1相关；(

) ovarian cancer on MUC1; (

) 卵巢癌与MUC1相关；(

) prostate cancer on MUC1; (

) 前列腺癌在MUC1上；(

) gastric cancer on MUC1; (

) 胃癌关于MUC1; (

) lung cancer on MUC1.

`) 肺癌与MUC1的关系。`

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Discussion

讨论

We successfully constructed a detection method for breast cancer cells via aptamer recognition of MUC1 using ICP-MS and fluorescence imaging. Subsequently, we utilized the two-sample MR approach to explore the relationship between breast cancer and liver cancer with respect to MUC1. As reported

我们成功构建了一种通过适配体识别MUC1并利用ICP-MS和荧光成像检测乳腺癌细胞的方法。随后，我们利用两样本MR方法探讨了乳腺癌与肝癌在MUC1方面的关系。据报道

, mucins such as MUC1 are targets in immunotherapy for various tumors (e.g., breast, pancreas, ovary, etc.). MUC1 can not only serve as a detection site but also as a target for drug delivery

，MUC1等粘蛋白是各种肿瘤（如乳腺、胰腺、卵巢等）免疫治疗的靶点。MUC1不仅可以作为检测位点，还可以作为药物递送的靶点。

, enabling precise medication administration. Therefore, this study further investigates the relationship between other types of cancer and MUC1.

，能够实现精确的药物管理。因此，本研究进一步探讨了其他类型癌症与MUC1的关系。

Existing research has indicated that during the development of cancer, MUC1 can suppress cell proliferation through a β-catenin-dependent mechanism

现有研究表明，在癌症发展中，MUC1可以通过β-连环蛋白依赖性机制抑制细胞增殖。

. Specifically, the interaction between the cytoplasmic tail of MUC1 and β-catenin significantly affects cell cycle proliferation, as MUC1 is located on the apical surface, while β-catenin is on the basolateral surface, thus this process hardly occurs in normally polarized epithelial cells

特别是，MUC1的胞质尾部与β-连环蛋白之间的相互作用显著影响细胞周期增殖，因为MUC1位于顶端表面，而β-连环蛋白位于基底侧表面，因此在正常极化的上皮细胞中这一过程几乎不会发生。

. Breast cancer is one of the greatest threats to global women’s health due to its high incidence and mortality rates

乳腺癌因其高发病率和死亡率成为威胁全球女性健康的最大隐患之一。

. Most of the existing literature has shown

。大多数现有文献已经表明

that MUC1 is highly expressed when breast cancer is present, which is also reflected in the experimental part of this paper where high expression of MUC1 on breast cancer cells MCF-7 is demonstrated. In the two-sample Mendelian randomization study, we found a potential negative correlation between breast cancer and the expression of MUC1 (P.

当存在乳腺癌时，MUC1高度表达，这在本文的实验部分也有所体现，其中展示了乳腺癌细胞MCF-7上MUC1的高表达。在两样本孟德尔随机化研究中，我们发现乳腺癌与MUC1表达之间存在潜在的负相关关系（P值）。

IVW

<0.05), a result consistent with the findings mentioned by Emad et al.

<0.05），这一结果与Emad等人提到的发现一致。

, who noted that the expression of MUC1 is negatively correlated with the tumor histological grade and tumor size in breast cancer, indicating that while MUC1 is overexpressed, its expression is inversely related to the tumor histological grade and size. Liver cancer is one of the leading causes of cancer-related deaths worldwide, as it was responsible for approximately 830,000 deaths globally in 2020, with an expected increase in incidence to over 1 million by 2025.

，该研究表明 MUC1 的表达与乳腺癌的肿瘤组织学分级和肿瘤大小呈负相关，这表明虽然 MUC1 表达上调，但其表达水平与肿瘤组织学分级和大小成反比。肝癌是全球癌症相关死亡的主要原因之一，2020 年全球约有 83 万人死于肝癌，预计到 2025 年其发病率将增加至超过 100 万。

. In a study by Yoshinori et al.

。在Yoshinori等人的研究中

on the application of one of the MUC1 proteins, KL-6 mucin, in gastrointestinal cancer, liver cancer, and pancreatic cancer, no expression of MUC1 was detected in liver cancer cells. This is consistent with the findings of MR study (P

关于MUC1蛋白之一KL-6黏蛋白在胃肠道癌、肝癌和胰腺癌中的应用，未检测到肝癌细胞中MUC1的表达。这与MR研究的结果一致（P

IVW

>0.05).This also suggests that there is no overexpression of MUC1 protein in liver cancer cells. As demonstrated in our experimental section, we can use HepG2 cells as a control cell line for the experiment, and the MR results are consistent with those from the experimental section.

大于0.05）。这同样表明肝癌细胞中MUC1蛋白没有过表达。正如我们在实验部分所展示的，我们可以使用HepG2细胞作为实验的对照细胞系，并且磁共振结果与实验部分的结果一致。

Colorectal cancer (CRC) is one of the most common types of cancer among both men and women globally, ranking as the third most common cancer worldwide

结直肠癌（CRC）是全球男性和女性中最常见的癌症类型之一，位居全球第三大常见癌症。

. According to data from the American Cancer Society, the lifetime risk of developing colorectal cancer in 2020 was 4.3% for men and 4.0% for women, accounting for 10% of new cases and 9.4% of total cancer-related deaths. The incidence of colorectal cancer is projected to continue to increase in the future.

根据美国癌症协会的数据，2020年男性和女性终生患结直肠癌的风险分别为4.3%和4.0%，占新发病例的10%和癌症相关死亡总数的9.4%。预计未来结直肠癌的发病率将继续上升。

. Studies have suggested that MUC1 may serve as an unfavorable prognostic marker, and its upregulation may be associated with the progression of colorectal cancer

研究表明，MUC1可能作为不良预后标志物，其上调可能与结直肠癌的进展有关。

. Additionally, a retrospective study of 202 patients who underwent surgery for colorectal cancer (CRC) also showed abnormally high mRNA and protein expression of MUC1 in tumor tissues. These results indicate that the expression of MUC1 may be a biomarker for poor prognosis in colorectal cancer and may play a role in tumor transformation and metastasis.

此外，对202例接受结直肠癌（CRC）手术的患者进行的回顾性研究也显示肿瘤组织中MUC1的mRNA和蛋白表达异常增高。这些结果表明，MUC1的表达可能是结直肠癌预后不良的生物标志物，并可能在肿瘤转化和转移中发挥作用。

. Zeng et al., in a study assessing the correlation between MUC1 and colorectal cancer using data from PubMed/MEDLINE and EMBASE, also demonstrated that the pooled data indicated a significant association between MUC1 expression and the metastasis of colorectal cancer

曾等人在一项使用PubMed/MEDLINE和EMBASE数据评估MUC1与结直肠癌相关性的研究中也表明，汇总数据显示MUC1表达与结直肠癌的转移之间存在显著关联。

. This is consistent with the findings of our Mendelian Randomization (MR) study (P

. 这与我们的孟德尔随机化（MR）研究结果一致（P

IVW

< 0.05), and it also provides a novel approach for clinical detection.

< 0.05），并且为临床检测提供了新的方法。

Ovarian cancer is the most lethal of gynecological cancers and the eighth most common cancer among women globally

卵巢癌是妇科癌症中最致命的一种，也是全球女性中第八常见的癌症。

. Studies have indicated that autoantibodies to MUC1 have prognostic value for poor clinical response and reduced overall survival in ovarian cancer

研究表明，针对MUC1的自身抗体对卵巢癌的临床反应差和总体生存率降低具有预后价值。

. Ma et al.

。马等

also demonstrated in a study that MUC1 is significantly overexpressed in ovarian cancer cells and regulates the AKT signaling pathway by upregulating the expression of EGFR. Within the scope of our search, no studies have been found that analyze the association between colorectal cancer and MUC1 using a two-sample bidirectional MR approach.

同样在一项研究中证明，MUC1在卵巢癌细胞中显著过表达，并通过上调EGFR的表达来调节AKT信号通路。在我们的搜索范围内，尚未发现使用两样本双向孟德尔随机化方法分析结直肠癌与MUC1之间关联的研究。

This study also shows, using the two-sample MR method, that MUC1 is a prognostic marker related to colorectal cancer (P.

本研究还使用两样本MR方法表明，MUC1是与结直肠癌相关的预后标志物 (P。

IVW

<0.05). For cancer cells with high expression of MUC1, it can not only play an important role in the early detection and prognosis monitoring of cancer, but also carry out tumor treatment research as the target molecule of tumor targeted therapy.

<0.05）。对于MUC1高表达的癌细胞，它不仅可以在癌症的早期检测和预后监测中发挥重要作用，还可以作为肿瘤靶向治疗的靶分子进行肿瘤治疗研究。

Additionally, we investigated the relationships between MUC1 and prostate cancer, gastric cancer, lung cancer, basal cell carcinoma, and esophageal adenocarcinoma. The Mendelian Randomization (MR) analysis results indicate that there is no significant association between MUC1 and the aforementioned types of cancer(P.

此外，我们研究了MUC1与前列腺癌、胃癌、肺癌、基底细胞癌和食管腺癌之间的关系。孟德尔随机化（MR）分析结果显示，MUC1与上述癌症类型之间没有显著关联（P）。

IVW

>0.05). Prostate cancer is the second most common cancer in men and the fifth leading cause of cancer-related deaths

>0.05）。前列腺癌是男性中第二常见的癌症，也是癌症相关死亡的第五大原因

. Studies have shown that the MUC1/Y subtype is highly expressed in prostate cancer cells

研究表明，MUC1/Y亚型在前列腺癌细胞中高表达。

. Gastric cancer is a highly heterogeneous disease with high incidence and mortality rates worldwide

胃癌是一种高度异质性的疾病，在世界范围内具有很高的发病率和死亡率。

. In a retrospective study assessing the prognostic role of MUC1 expression in American gastric cancer

在一项评估MUC1表达在美国胃癌中预后作用的回顾性研究中

, MUC1 was found to be a useful prognostic biomarker for predicting gastric cancer outcomes. However, their immunohistochemical results showed that the probability of MUC1 positivity was 71.4%, indicating that not all patients are MUC1-positive. Lung cancer

，MUC1被发现是预测胃癌结果的有用预后生物标志物。然而，他们的免疫组化结果显示，MUC1阳性的概率为71.4%，表明并非所有患者都为MUC1阳性。肺癌

is the most common cause of cancer-related deaths globally, with the majority of cases being diagnosed at advanced stages requiring systemic treatment. Savarese-Brenner et al.

是全球癌症相关死亡最常见的原因，大多数病例在晚期被诊断出来，需要系统性治疗。萨瓦雷塞-布伦纳等。

demonstrated that both MUC1 and CD147, these two markers, are highly expressed in patient-derived small cell lung cancer and small cell lung cancer circulating tumor cell lines, although small cell lung cancer accounts for only about 15% of cases. In a review on the role of mucin expression in the diagnosis of esophageal cancer.

证明了MUC1和CD147这两个标记物在患者来源的小细胞肺癌和小细胞肺癌循环肿瘤细胞系中均高表达，尽管小细胞肺癌仅占约15%的病例。在一篇关于黏蛋白表达在食管癌诊断中的作用的综述中。

, multiple literature sources elaborated on the high expression of MUC1 in Barrett’s esophageal adenocarcinoma.The above results differ from those of the bidirectional two-sample MR in this study, possibly due to regional differences in data sources, as the summary data analyzed in this study mostly come from European populations.

，多篇文献阐述了MUC1在巴雷特食管腺癌中高表达。以上结果与本研究的双向两样本MR结果不同，可能由于数据来源的地区差异，因为本研究分析的汇总数据多来自欧洲人群。

It may also be because the phenotype or genotype of high MUC1 expression is relatively rare in the summary data, such as in lung cancer and esophageal adenocarcinoma. Another possibility is that the results differ from our two-sample MR findings due to interference from external physical, chemical, and biological factors..

这也可能是因为在汇总数据中，高MUC1表达的表型或基因型相对较少，例如在肺癌和食管腺癌中。另一种可能性是由于外部物理、化学和生物因素的干扰，结果与我们的两样本MR研究结果不同。

This study possesses several strengths. Firstly, it combines methodological detection methods with Mendelian randomization analysis, enhancing the credibility and rigor of the research. Additionally, the study introduces a novel detection method for breast cancer cells, significantly increasing the credibility of the results through quantitative detection and fluorescence imaging.

本研究具有多个优势。首先，它将方法学检测方法与孟德尔随机化分析相结合，增强了研究的可信度和严谨性。此外，该研究引入了一种新颖的乳腺癌细胞检测方法，通过定量检测和荧光成像显著提高了结果的可信度。

Utilizing carbon quantum dots for imaging, as opposed to traditional fluorescent materials such as FAM, offers longer fluorescence lifetimes and stronger resistance to interference. Secondly, the study explores the relationship between exposure and outcome at the genetic level, which can substantially reduce confounding bias, further enhancing the credibility of the results.

利用碳量子点进行成像，相比传统的荧光材料如FAM等，具有更长的荧光寿命和更强的抗干扰能力。其次，该研究在基因层面上探讨暴露与结局的关系，可大大减少混杂偏倚，进一步提高结果可信度。

Moreover, the study employs methods such as linkage disequilibrium clustering, heterogeneity testing, horizontal pleiotropy testing, and the leave-one-out method to assess data, thereby further confirming the stability of the causal relationship. However, this study also has certain limitations, which may be one of the main reasons for the differences between the results of this study and published literature.

此外，该研究还采用了连锁不平衡聚类、异质性检验、水平多效性检验和留一法等方法对数据进行评估，从而进一步证实了因果关系的稳定性。然而，本研究也存在一定的局限性，这可能是导致本研究结果与已发表文献结果存在差异的主要原因之一。

Firstly, the population in this study is primarily of European descent, which may limit its generalizability. Secondly, as the study is based on large-scale GWAS analysis, it cannot rule out the impact of factors such as psychology, age, and health status on the study outcomes..

首先，本研究中的人口主要是欧洲血统，这可能限制了其普遍性。其次，由于该研究基于大规模的GWAS分析，因此不能排除心理、年龄和健康状况等因素对研究结果的影响。

Conclusion

结论

This study successfully developed a method based on a nanogold/carbon dot dual-functional probe that recognizes the MUC1 protein on the cell surface to further identify breast cancer cells MCF-7, with liver cancer cells HepG2 selected as control cells. Furthermore, we validated the high expression of MUC1 in breast cancer using two-sample MR (P.

本研究成功开发了一种基于纳米金/碳点双功能探针的方法，该探针识别细胞表面的MUC1蛋白，以进一步鉴定乳腺癌细胞MCF-7，并选择肝癌细胞HepG2作为对照细胞。此外，我们使用两样本MR验证了MUC1在乳腺癌中的高表达（P。

IVW

< 0.05), and the absence of MUC1 expression in liver cancer cells (P

< 0.05），以及肝癌细胞中MUC1表达的缺失（P

IVW

> 0.05). Additionally, we found a potential positive correlation between colorectal cancer and ovarian cancer with MUC1 (P

> 0.05）。此外，我们发现结直肠癌和卵巢癌与MUC1之间存在潜在的正相关关系（P

IVW

< 0.05), suggesting that MUC1 may also be a potential diagnostic biomarker for colorectal and ovarian cancers.

< 0.05），这表明MUC1也可能成为结直肠癌和卵巢癌的潜在诊断生物标志物。

Data availability

数据可用性

The experiment datasets generated and analyzed during the current study are available from the corresponding author on reasonable request. The GWAS data of breast cancer , liver cancer, colorectal cancer, ovarian cancer, prostate cancer, gastric cancer and lung cancer accessible under application at https://www.ebi.ac.uk/gwas/ (accessed on April 2024), and handling of these data are described in Materials and Methods..

当前研究中生成和分析的实验数据集可根据合理要求从通讯作者处获取。乳腺癌、肝癌、结直肠癌、卵巢癌、前列腺癌、胃癌和肺癌的GWAS数据可通过https://www.ebi.ac.uk/gwas/申请访问（截至2024年4月），这些数据的处理方法在材料与方法部分有描述。

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Acknowledgements

致谢

The authors express sincere gratitude to the researchers and participants involved in the original GWASs for their efforts in collecting and managing the large-scale data resources.

作者对参与原始GWAS的研究人员和参与者表示诚挚的感谢，感谢他们为收集和管理大规模数据资源所做出的努力。

Funding

资金

This study was supported by the National Natural Science Foundation of China (Grant No. 22304025), and the Natural Science Foundation of Fujian Province, China (Grant No. 2021J01727).

本研究得到了中国国家自然科学基金（批准号：22304025）和福建省自然科学基金（批准号：2021J01727）的支持。

Author information

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Author notes

作者笔记

Zhuzheng Wu, Qingquan Chen and Zhifeng Lin contributed to this work equally.

吴竺铮、陈清泉和林志峰对这项工作做出了同等贡献。

Authors and Affiliations

作者和所属机构

Department of Health Inspection and Quarantine, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China

福建医科大学公共卫生学院卫生检验检疫系，福州，福建，中国

Zhuzheng Wu, Yating Chen, Xiaohao Gan & Ye He

吴主正，陈雅婷，甘晓浩，何烨

Department of Public Health and Medical Technology, Xiamen Medical College, Xiamen, Fujian, China

中国福建省厦门市厦门医学院公共卫生与医学技术系

Zhuzheng Wu

吴珠铮

The School of Public Health, Fujian Medical University, Fuzhou, 350108, Fujian Province, China

中国福建省福州市福建医科大学公共卫生学院，邮编350108

Qingquan Chen & Zhifeng Lin

陈清泉和林志峰

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Zhuzheng Wu

吴珠政

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陈清泉

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甘小浩

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Contributions

贡献

Conceptualization and methodology, Ye He; writing—original draft preparation, Zhuzheng Wu; writing—review and editing, Qingquan Chen and Zhifeng Lin; validation, Yating Chen and Xiaohao Gan; formal analysis, Qingquan Chen and Zhuzheng Wu. All authors have read and agreed to the published version of the manuscript..

概念化与方法论，何烨；初稿撰写，吴竺正；审阅与编辑，陈清泉和林志峰；验证，陈雅婷和甘小豪；正式分析，陈清泉和吴竺正。所有作者均已阅读并同意发表的手稿版本。

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Correspondence to

致信

Ye He

叶赫

。

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Wu, Z., Chen, Q., Lin, Z.

吴，陈，林