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Abstract

Objective: To predict the pharmacodynamic material basis and mechanism of Chinese medicinal mushroom Sanghuangporus vaninii (Ljub.) L.W. Zhou & Y.C. Dai (SV) against breast cancer based on ultraperformance liquid chromatography tandem quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) and network pharmacology. Methods: We explored the compositional basis of SV using UPLC-Q-TOF/MS, then the potential targets and key pathways involved in the anti-breast cancer effect were predicted using a network pharmacology approach. Molecular docking was performed with the key compounds and the hub targets to confirm the results of the network pharmacology screening. Results: A total of 53 chemical components were identified, including 4 organic acids, 6 catechins, 13 pyranones, 13 flavonoids, and 17 fatty acids. 33 polyphenols and 144 corresponding targets were found to be significantly associated with its anti-breast cancer activity. Molecular docking results showed that the core compound could significantly bind to the core target. Conclusion: The anti-proliferative effect of SV against breast cancer could be attributed to a combination of multi-component, multi-target, and multi-channel mechanisms. The key active compound of SV in the treatment of breast cancer may be phellibaumin B, naringenin, hesperetin, sterubin, phelligrin A and phelligrin C, and the molecular mechanism may be related to the key targets MMP9, EGF, and EGFR, and that signaling pathways such as MAPK and PI3K-Akt may be responsible for SV-induced growth inhibition in breast cancer cells.

Keywords

UPLC-Q-TOF/MS network pharmacology anti-breast cancer molecular docking

Introduction

Breast cancer (BRCA) is a significant public-health issue due to its prevalence, ranking as the second leading cause of cancer-related death among women both in China and worldwide.¹ Current multidisciplinary therapeutic options for BRCA, including surgery, chemotherapy, adjuvant therapy, and radiotherapy, are limited due to various effects, such as recurrence, resistance, and toxic side effects.² Natural mushroom-derived medicines, particularly those derived from Sanghuangporus vaninii, a large precious medicinal mushroom known as “Yanghuang” in China, are gaining more attention in BRCA treatment due to their advantages of efficiency, safety, and minimal side effects.^3,4 This mushroom, which primarily grows on the trunk of Populus spp. in northeastern China, Korea, and other East Asian countries, has long been employed in the treatment of tumor-related diseases, including breast, oral, gastrointestinal, lung, and colon cancers.^5,6 In recent years, there have been promising pharmacological studies on its antitumor activity, antioxidant effect, anti-inflammatory effect, uric acid lowering, etc.⁷ Yu et al reported that the aqueous extracts of SV inhibited the proliferation of A375 human melanoma cells in a dose-dependent manner, and induced A375 cell cycle arrest in S phase and apoptosis by up-regulating p21 expression.⁸ Wan et al studied that the polysaccharides of SV inhibited the proliferation of non-small cell lung cancer cell lines A549, 95-D and NCI-H460, especially the acidic polysaccharide affected cell morphology and colony formation in NCI-H460 cells, and its antitumor regulation via activation of the p53 signaling pathway in breast cancer MCF-7 cells.^9,10 Qiu et al reported that SV extract could induce apoptosis in HT-29 cells via the intrinsic apoptotic pathway, and further found that a pyrone inoscavin A isolated from a SV extract exhibited anti-colon cancer activity via the hedgehog signaling pathway.¹¹ He et al reported that SV significantly inhibited the proliferation of SiHa cells. Cell cycle blockade and induction of cell apoptosis contributed to the cell death induced by SV.¹² Our recent studies have demonstrated that polyphenolic compounds from Sanghuangporus and Inonotus sp. exhibit significant antitumor activities against breast cancer and sedative effects.¹³ However, the specific active components and the underlying mechanisms of their anti-proliferative effects against breast cancer remain unclear.

The comprehensive investigation of active chemical constituents and mechanisms of action is essential due to the synergistic multi-component effects exhibited by natural mushroom medicines. To achieve this objective, it is crucial to select a reasonable and efficient analytical method that can provide rapid analysis while ensuring rich and accurate data. Ultra-performance liquid chromatography quadruple detection systems are an appropriate analytical tool with high resolution, excellent sensitivity, and strong structural characterization capability. Furthermore, they enable effective separation and analysis of complex components.¹⁴ With the rapid advancements in bioinformatics, network pharmacology has emerged as a powerful tool for exploring the multiple molecular aspects of medicine. By combining ultraperformance liquid chromatography tandem quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) with network pharmacology, a systematic understanding of the active chemical constituents and their mechanisms of action can be obtained.¹⁵

In this study, UPLC-Q-TOF/MS combined with network pharmacology was employed for rapid qualitative analysis of the chemical compositions and elucidation of anti-breast cancer mechanisms. The results will serve as a theoretical basis for further quality evaluation and application of S. vaninii.

Results

Chemical Composition

Members of the genera Sanghuangporus and Inonotus have been reported to produce a variety of yellow polyphenol pigments, known as styrylpyrones, which have shown significant biological effects. The structure of styrylpyrones contains more than 4 phenolic hydroxyl groups, which they are acidic and have a high ionization efficiency in the negative ion mode.¹⁶ So the negative ion mode was utilized to analyze the chemical constituents of ethanol extracts of SV, and compounds were identified based on their chromatographic peak retention time, accurate relative molecular mass, MS fragmentation, as well as relevant literature. Isomers were distinguished by their characteristic MS² fragmentation patterns reported in the literature. Figure 1 displays the full scan ESI-MS spectra in negative ion mode. Although the base peak ion (BPI) is complex, most of the chromatographic peaks are well separated. A total of 53 chemical components including 4 organic acids, 6 catechins, 13 pyranones, 13 flavonoids and 17 fatty acids were detected and identified unambiguously or tentatively. The detailed results can be found in Table 1.

(1) Organic acid. In mass spectrometry of organic acids, characteristic fragments are mainly obtained by loss of carboxyl group in negative ion mode. SV 1 showed a [M-H]− at m/z 191.0190 (C₆H₈O₇), along with two fragment ions at m/z 147.0284 [M-H-CO₂]− and 103.0029 [M-H-2CO₂]−, which were assumed to be citric acid. Fragment ions of SV 2 at m/z 153.0180 [M-H-OH]−, 125.0233 [M-H-CO₂]− and 109.0278 [M-H-CO₂-OH]− were formed, which was identified as gallic acid. SVs 3 and 4 showed precursor ions at m/z 153.0183 [M-H]− (C₇H₆O₄) and m/z 137.0233 [M-H]− (C₇H₆O₃), respectively. Characteristic fragment ions at m/z 109.0292 and 108.0188 formed due to loss of carboxyl (44 Da) and aldehyde group (29 Da), respectively. These fractions were identified as protocatechuic acid and protocatechuic aldehyde based on the above results and literature.¹¹

(2) Catechins. Six catechins were identified from the SV extracts generating a characteristic fragment ion at m/z 289. SVs 5 and 6 had same molecular ion peak at m/z 457 [M-H]− (C₂₂H₁₈O₁₁), the fragment ions at m/z 305.0703 and 289.0665 represented the loss of galloyl (152 Da) and gallic acid (169 Da), which were identified as gallocatechin gallate and epigallocatechin gallate based on the fragmentation rule and retention time together with the literature.¹⁷ The mass spectrum of SVs 7 and 8, showed a strongly protonated molecular ion at m/z 289.0706 [M-H]− (C₁₅H₁₄O₆), and fragment ions at m/z 245.0822 [M-H-CO₂]− and 217.0465 [M-H-CO₂-CO]− were detected. Moreover, its fragment ion peak at m/z 137.0242, corresponding to the A-ring fragment produced by a retro Diels-Alder reaction, was characteristic of catechin and epicatechin.¹² The molecular ions of SVs 9 and 10 were at m/z 441.0809 [M-H]− (C₂₂H₁₈O₁₀), they had the same distribution of precursor and fragment ions, the fragment ion at m/z 289.0682 indicated the loss of galloyl (152 Da). In combination with the information from the literature,¹⁷ they were identified as catechin gallate and epicatechin gallate.

(3) Styrylpyrones, mainly composed of the hispidin skeleton, were identified as the main polyphenolic composition in the SV extract. Their characteristic fragment ions in negative mode were m/z 243 (C₁₃H₇O₅₋), 159 (C₁₀H₇O₂₋) and 135 (C₈H₇O₂₋). A total of 13 styrylpyrones were identified, among which SV 11 exhibited an [M-H]− ion at m/z 177.0553 (C₁₀H₁₀O₃), and produced fragment ions at m/z 161.0253 [M-H-OH]− and 134.0370 [M-H-C₂H₃O]−, which were consistent with 4-(3,4-dihydroxyphenyl)-3-buten-2-one.¹⁸ The mass spectra of SV 12 showed a peak of molecular ion at 975.1425 [M-H]− (C₅₂H₃₂O₂₀) and fragment ions at m/z 487.0592 [M-H-C₂₆H₁₆O₁₀]− and 243.0293 (C₁₃H₇O₅₋) due to successive losses of a series of hispidin units, and was polymerized with four hispidin molecules, identified as phelligridimer A in literature.¹⁹ SV 13 and 14 were isomers with the same protonated ion [M-H]− at m/z 463 (C₂₅H₂₀O₉) and [2M-H]− at m/z 927, which produced fragment ions at m/z 405.0605 [M-H-C₃H₆O]−, 379.0827 [M-H-CH₃-CO-CH-CO]−, 259.0606 [M-H-C₆H₅O₂-C₅H₃O₂]−, 243.0299 [M-H-C₆H₅O₂-C₆H₇O₂]−. Characteristic fragments at m/z 201.0602, 159.0441, 135.0440 were also detected. In the results, the isomers were consistent with davallialactone and interfungin A on the basis of the retention times, respectively.¹⁹ SV 15 produced predominant fragments at m/z 463.0996, 405.0528, 379.0804, 243.0279, 159.0434, and 135.0433, suggesting that its structure is similar to davallialactone, but has a molecular weight difference of 58 (C₂H₂O₂), which was in agreement with baumin compared to literature information.²⁰ The SV 16 showed a [M-H]− at m/z 423.1662 (C₂₂H₁₆O₉) and [2M-H]− at m/z 847.3334, indicating that its molecular weight (424) was equal to phellibaumin B or D. Meanwhile, the fragment ion at m/z 243.0297 was formed by the loss of caffeic acid in the MS² spectrogram.²¹

Figure 1.

Base peak ion (BPI) of ethanol extract from S. vaninii fruit body in negative ion mode.

Table 1.

Identification of Constituents in the Ethanolic Extract of S. vaninii by UPLC-Q-TOF-MS in Negative Ion Mode.

No.	Classify	t_R (min)	Molecular ion (m/z)	Molecular formula	Fragmentation (m/z)	Compound
SV 1	Organic acids	1.38	191.0190	C₆H₈O₇	147.0284, 103.0029	Citric acid
SV 2		2.86	169.0132	C₇H₆O₅	125.0242, 109.0278	Gallic acid
SV 3		5.40	153.0183	C₇H₆O₄	137.0233, 109.0292	Protocatechuic acid
SV 4		7.32	137.0235	C₇H₆O₃	108.0188	Protocatechuic aldehyde
SV 5, SV 6	Catechins	8.91, 12.18	289.0713, 289.0706	C₁₅H₁₄O₆	245.0822, 217.0465, 169.0236, 125.0236	Catechin, Epicatechin
SV 7, SV 8		11.44, 12.95	457.0789, 457.0764	C₂₂H₁₈O₁₁	305.0703, 289.0665, 169.0139, 125.0238	Gallocatechin gallate, Epigallocatechin gallate
SV 9, SV 10		14.97, 15.89	441.0809, 441.0821	C₂₂H₁₈O₁₀	289.0682, 271.0570, 169.0126, 125.0228	Catechin gallate, Epicatechin gallate
SV 11	Pyranones	14.23	177.0553	C₁₀H₁₀O₃	161.0253, 134.0370, 125.0231, 108.0216	4-(3,4-Dihydroxyphenyl)-3-buten-2-one
SV 12		17.81	975.1425	C₅₂H₃₂O₂₀	487.0592, 405.0547, 379.0826, 243.0293, 159.0443, 135.0451	Phelligridimer A
SV 13, SV 14		18.30, 18.86	463.1034, 463.1045	C₂₅H₂₀O₉	405.0605, 379.0827, 259.0606, 243.0299, 159.0441, 135.0440	Davallialactone, Interfungin A
SV 15		18.93	521.1085	C₂₇H₂₂O₁₁	463.0996, 405.0528, 379.0840, 243.0279, 159.0434, 135.0433	Baumin
SV 16		21.80	423.1662	C₂₂H₁₆O₉	379.0877, 243.0297, 135.0460	Phellibaumin B or D
SV 17		23.12	489.0802	C₂₆H₁₈O₁₀	445.0937, 403.0804, 377.0623, 359.0533, 335.0521, 2430307, 241.0495, 159.0433, 135.0432	Hypholomine B
SV 18		23.77	461.0866	C₂₅H₁₈O₉	377.0649, 271.0700, 257.0425, 243.0310, 159.0416, 135.0480	Inoscavin A
SV 19		27.42	379.0448	C₂₀H₁₂O₈	285.0387, 269.0030, 243.0310, 217.0496, 159.0425, 135.0457	Phelligridin D
SV 20		28.13	477.1202	C₂₆H₂₂O₉	445.0906, 377.0665, 243.0250, 159.0433, 135.0478	Phelligridin F
SV 21		28.56	395.0773	C₂₁H₁₆O₈	351.2119, 289.0719, 271.0570, 243.0299, 159.0458, 135.0455	Inoscavin D
SV 22		29.45	363.0516	C₂₀H₁₂O₇	345.2270, 281.1335, 225.1998, 159.0434, 135.0431	Phelligridin C
SV 23		30.29	435.1105	C₂₄H₂₀O₈	403.0831, 379.1123, 273.0757, 243.0289, 159.0446, 135.0471	Inoscavin B
SV 24	Flavonoids	15.62	235. 0598	C₁₂H₁₂O₅	217.0116, 199.0390, 151.0050, 135.0440, 125.0223	Decarboxyhydroxycitrinone
SV 25		17.81	287.0561	C₁₅H₁₂O₆	259.0600, 243.0293, 151.0024	Aromadendrin
SV 26		23.98	271.0608	C₁₅H₁₂O₅	243.0291, 151.0023, 119.0499	Naringenin
SV 27, SV 28		25.87, 27.10	301.0721, 301.0718	C₁₆H₁₄O₆	285.0375, 273.0756, 178.9974, 151.0014	Hesperetin, Sterubin
SV 29		27.78	393.0973	C₂₂H₁₈O₇	377.0580, 365.1040, 287.0522, 259.0592, 243.0597, 151.0029	Gericudranin E
SV 30		29.84	285.0765	C₁₆H₁₄O₅	271.0605, 255.0243, 243.0303, 165.0187, 151.0029, 119.0493	Sakuranetin
SV 31, SV 32		32.62	377.1045	C₂₂H₁₈O₆	283.0615, 271.0610, 151.0033, 119.0499	Phelligrin A and B
SV 33, SV 34		32.84, 33.42	391.1205, 391.1187	C₂₃H₂₀O₆	377.1144, 283.0621, 271.0629, 151.0012, 119.0493	Methylphelligrin A and B
SV 35		33.54	499.1420	C₂₉H₂₄O₈	393.0976, 365.1065, 287.0537, 259.0617, 151.0012, 119.0263	Gericudranin D
SV 36		37.10	483.1432	C₂₉H₂₄O₇	389.1027, 377.1008, 283.0605, 271.0589, 151.0033, 119.0490	Phelligrin C
SV 37	Fatty acids	31.64, 35.24	329.2316	C₁₈H₃₄O₅	171.1024, 157.0861	Trihydroxy-octadecenoic acid
SV 38		37.74, 38.10	313.2401	C₁₈H₃₄O₄	285.2091, 183.1391	Octadecanedioic acid
SV 39		39.83	285.2068	C₁₆H₃₀O₄	267.1943, 223.2068	Hexadecanedioic acid
SV 40		40.40, 45.15	271.2281	C₁₆H₃₂O₃	271.2277	Hydroxy-hexadecanoic acid
SV 41		41.21	311.2227	C₁₈H₃₂O₄	249.2219	Octadecenedioic acid
SV 42		41.79	297.2433	C₁₈H₃₄O₃	297.2432	Hydroxy-octadecenoic acid
SV 43		46.19	279.2328	C₁₈H₃₂O₂	279.2324	Octadecadienoic acid
SV 44		46.87	369.3005	C₂₂H₄₂O₄	307.3013	Phellogenic acid
SV 45		47.16	255.2321	C₁₆H₃₂O₂	–	Hexadecanoic acid
SV 46		47.27	355.3215	C₂₂H₄₄O₃	355.3210	Hydroxy-docosanoic acid
SV 47		47.48	281.2474	C₁₈H₃₄O₂	255.2329	Octadecenoic acid
SV 48		48.38	397.3325	C₂₄H₄₆O₄	335.3319	Tetracosanedioic acid
SV 49		48.86	283.2639	C₁₈H₃₆O₂	–	Octadecanoic acid
SV 50		51.34	339.3260	C₂₂H₄₄O₂	–	Docosanoic acid
SV 51		52.39	367.3560	C₂₄H₄₈O₂	367.3540	Tetracosanoic acid
SV 52		52.96	381.3737	C₂₅H₅₀O₂	381.3712	Pentacosanoic acid
SV 53		53.59	395.3889	C₂₆H₅₂O₂	395.3888	Hexacosanoic acid

t_R, retention times.

For SV 17, the mass spectra exhibited [M-H]− at m/z 489.0802 (C₂₆H₁₈O₁₀) and [2M-H]− at m/z 979.1697 for the precursor ion, generating a series of predominant product ions at m/z 445.0937 [M-H-CO₂]−, 403.0804 [M-H-C₃H₂O₃]−, 377.0623 [M-H-C₅H₄O₃]−, 335.0521 [M-H-C₈H₉O₂-OH]− and 241.0495 [M-H-C₈H₉O₂-C₅H₃O₃]−. Two additional characteristic pyranone fragment ions were observed at m/z 159.0457 and 135.0444. In combination with the information in the literature,¹⁹ it was identified as hypholomine B. SV 18 produced an [M-H]− ion at m/z 461.0866 (C₂₅H₁₈O₉) and gave fragment ions at m/z 377.0649 [M-H-C₄H₄O₂]−, 271.0600 [M-H-C₆H₅O₂-C₄HO₂]−, 257.0425 [M-H-C₆H₅O₂-C₅H₃O₂]− and 243.0310 [M-H-2C₆H₅O₂]−. Moreover, characteristic fragments were detected at m/z 201.0602, 159.0416, and 135.0480, which were assigned as inoscavin A with literature information.¹⁹ SV 19 produced a precursor ion at m/z 379.0448 [M-H]− (C₂₀H₁₂O₈) and an [2M-H]− ion at m/z 759.0884, and fragment ions of the receptacle at m/z 351.0427 [M-H-CO]−, 335.0443 [M-H-CO-OH]−, 269.0030 [M-H-C₆H₆O₂]−, together with several product ions (at m/z 243.0310, 217.0496, 159.0425, 135.0457) were observed. On the basis of these data and previous literature reports,²² it was identified as phelligridin D. The mass spectrum of SV 20 showed the molecular ion peak at m/z 477.1202 [M-H]− (C₂₆H₂₂O₉) and characteristic fragment ions at m/z 446.0906 [M-H-CH₃O]- was formed by loss of the methoxy group, m/z 405.0572 [M-H-C₃H₅O-CH₃]- indicated the loss of methyl and isoacetone groups. The other fragment ions were detected at m/z 377.0665, 243.0250, 159.0433, and 135.0478, which were in good agreement with the reference isolated phelligridin F.²³ SV 21 showed a molecular ion at m/z 395.0773 [M-H]− and fragment ions at m/z 363.0528 [M-H-2OH]−, 285.0435 [M-H-C₆H₆O₂]−, and the characteristic fragment ion at m/z 243.0299 [M-H-C₈H₆O₃]− corresponding to the loss of the methyl and dihydroxybenzaldehyde groups, respectively. Consequently, SV 21 was identified as inoscavin D.¹⁸ The mass spectra of SV 22 showed a molecular ion peak at m/z 363.0516 [M-H]- (C₂₀H₁₂O₇) and fragment ions at m/z 345.2270 [M-H-OH]−, 281.1335 [M-H-C₄H₃O₂]−, 225.1998 [M-H-C₇H₆O₃]−, 159.0434 [M-H-C₂₃H₁₂O₁₁]− and 135.0430, corresponding to phelligridin C.²⁴ The molecular ion peak of SV 23 was observed at m/z 435.1105 [M-H]− (C₂₄H₂₀O₈) and its characteristic fragment at m/z 403.0831[M-H-CH₃-OH]−, 273.0757 [M-H-C₉H₆O₃]−, 243.0289 [M-H-C₁₁H₁₂O₃]−, 159.0443 and 135.0430, which was identified as inoscavin B based on the pattern of the MS² fragment and literature.²⁵

(4) Flavonoids were detected in the wild fruit bodies of SV and exhibited strong fragment ions at m/z 151 and 119, corresponding to the A-ring fragment generated by a retro Diels-Alder reaction. The mass spectra of SV 24 showed fragment ions at m/z 217.0478 [M-H-H₂O]−, 203.0343 [M-H-2OH]−^, as well as characteristic fragment ions at m/z 151.0038 and 119.0482, which were identified as decarboxyhydroxycitrinone using the PubChem database. SV 25 displayed a molecular ion peak at m/z 287.0561 [M-H]- (C₁₅H₁₂O₆) along with fragment ions at m/z 259.0600 [M-H-CO]− and 243.0296 [M-H-CO-OH]−. The characteristic fragment ion at m/z 151.0024 was observed and identified as aromadendrin based on literature information.²⁶ SV 26 exhibited the molecular ion peak at m/z 271.0608 [M-H]− (C₁₅H₁₂O₅), along with characteristic fragment ions at m/z 243.0291 [M-H-CO]−, 151.0023 [M-H-C₄H₈O₄]− and 119.0499 [M-H-C₄H₈O₄-CH₃OH]−, its MS² fragment patterns were consistent with naringenin according to literature information.²⁶ SV 27 and 28 were isomers with the same protonated ion [M-H]− at m/z 301.0714 (C₁₆H₁₄O₆). In the results, they corresponded to hesperetin and sterubin, respectively.²⁷ Their identical MS² fragment patterns were very similar, producing predominant fragment ions at m/z 285.0375 and 273.0756 due to loss of CH₃ and CO together with fragments at m/z 178.9974, 151.0014. SV 30 was found to have a high abundance, and produced prominent ions at m/z 285.0765 [M-H]− (C₁₆H₁₄O₅), which fragment ions at m/z 271.0605 [M-H-CH₃]−, 255.0243 [M-H-CH₃-OH]−, 243.0303 [M-H-CH₃-CO]−, 165.0184, 151.0029, 119.0493 were detected, and matched well with sakuranetin.²⁷

SV 29, 31, 32, 33, 34, 35 and 36 exhibited similar fragmentation behavior with characteristic fragment ions at m/z 271 [M-H]− or 287 [M-H]−, in which the structure of the flavonoid core was mainly naringenin or aromadendrin. Among them, SVs 31 and 32 were isomers with the same protonated ion [M-H]− at m/z 377.1045. Fragment ions at m/z 283.0615 [M-H-C₆H₆O]− and 271.0610 [M-H-C₇H₆O]− were generated by the loss of one hydroxyl benzene and o-hydroxytoluene, respectively. In combination with the relevant literature,²¹ they were identified as phelligrins A and B. For SV 29, it gave the base peak at m/z 287.0522 [M-H-C₇H₆O]− due to the loss of o-hydroxytoluene and the fragments at the parent nucleus site were 16 Da (-OH) more than SV 31 or 32, in the result, it was assigned as gericudranin E. By comparing the fragment behavior of MS² with SV 31 and 32, it was found that SV 33 and 34 had the same fragmentation pattern, but they generated a 14-Da fragment ion (-CH₃) more than phelligrins A and B, so they were charachterized as methylphelligrin A and B.²¹ The mass spectrum of SV 35, exhibited a strongly protonated molecular ion at m/z 499.1420 [M-H]− (C₂₉H₂₄O₈) and produced prominent ions at m/z 393.0976 [M-H-C₇H₆O]− that representing the loss of the o-hydroxytoluene moiety (106 Da) from the molecular ion peak. The other fragmentation patterns were similar to SV 29, and its molecular formula was searched in the PubChem database, which was tentatively characterized as gericudranin D. The molecular ion peak of SV 36 was observed at m/z 483.1432 [M-H]- (C₂₉H₂₄O₇) and its characteristic fragment at m/z 389.1027 [M-H-C₆H₆O]−, 377.1008 [M-H-C₇H₆O]−, 283.0605 [M-H-C₇H₆O-C₆H₆O]− and 271.0589 [M-H-2C₇H₆O]− due to successive losses of hydroxylbenzene and o-hydroxytoluene. Meanwhile, it was found that SV 36 had the same fragmentation pattern with phelligrin A or B, but it differed by a mass number of 106 Da (C₇H₆O), so SV 36 was tentatively characterized as phelligrin C, which was searched by its structure against the chemical database SciFinder Scholar, and then considered as a new compound. The MS spectrum and the MS² fragmentation pathway of phelligrin C are shown in Figures 2 and 3.

(5) Fatty acids SV 37-53 were identified as fatty acids using the Lipidomics Gateway database, and the information is shown in Table 1.

Figure 2.

MS (A) and MS² (B) spectra of phelligrin C in negative ion mode.

Figure 3.

The possible mass spectroscopic fragmentation pathway of phelligrin C in negative ion mode.

Target Identifying and Prediction

In the present study, a total of 36 polyphenols (4 organic acids, 6 catechins, 13 pyranones, and 13 flavonoids) were obtained from the fruiting body of SV using UPLC-Q-TOF/MS. By searching the Swiss Target Prediction and TCMSP databases, after eliminating duplicates, there were 415 potential targets of 33 candidate compounds, ultimately suggesting that these compounds may have common bioactive targets and connecting networks. The other three compounds SV 12, 15 and 21 were searched without targets.

Breast Cancer Differentially Expressed Genes (BRCAdegs) Search

To explore the targets for breast cancer treatment, we screened differentially expressed genes (degs) between breast cancer and normal breast tissues using the Cancer Genome Atlas (TCGA) databases. A total of 5080 BRCAdegs were discovered with filtered by FDR < 0.05, including 2989 up-regulated genes and 2091 down-regulated genes. The volcano plot represented the relationship between the significance and the fold change of BRCAdegs (Figure 4). They were highlighted by red and blue dots (|log2 (fold change)| > 1), with red representing log2 (fold change) > 1 and blue representing log2 (fold change) < 1.

Figure 4.

The volcano diagram of BRCAdegs from TCGA. Red dots indicate up-regulated BRCAdegs, while blue dots indicate down-regulated BRCAdegs.

The Venn diagram showed the overlap of the compounds targets and BRCA-related DEGs (Figure 5), and 144 common targets were considered as potential targets of SV extracts against breast cancer.

Figure 5.

Venn diagram of the intersection potential targets of BRCAdegs and polyphenols from S. vaninii.

Network Construction and Analysis

To explore the relationship between the common targets, the 144 intersecting targets were imported into the STRING database and Cytoscape software for network visualization analysis, and the protein–protein interaction (PPI) network had a total of 142 nodes and 1188 edges, as shown in Figure 6. Then, using the CytoHubba plug-in unit for topological analysis according to betweenness, closeness and degree, that after the intersection of the top 10 core target genes (Figure 6A-C), 8 hub genes were screened out, namely MMP9, JUN, EGF, CCND1, IL6, ESR1, FOS and EGFR. These may be key targets in the anti-breast cancer effect of SV.

Figure 6.

Protein–protein interaction (PPI) network of total potential genes and the frequency of core genes, (A) betweenness-top10, (B) closeness-top10, (C) degree-top10.

The compound-target network was constructed using Cytoscape version 3.9.0. The network consisted of 175 nodes (31 compounds, 144 targets) and 525 interaction edges (Figure 7), resulting in an average degree of 6. In particular, the compounds with the top 6 in the compound-target network included SV26 (naringenin, degree = 45), SV27 (hesperetin, degree = 36), SV28 (sterubin, degree = 31), SV36 (phelligrin C, degree = 25), SV31 (phelligrin A, degree = 24), SV16 (phellibaumin B, degree = 24). The genes that were associated with the most compounds were CA12 (degree = 20), CA4 (degree = 18), ABCG2 (degree = 16), ESR1 (degree = 16), MMP9 (degree = 15), MMP12 (degree = 15). These high-level compounds and targets may play an important role in the anti-breast cancer effect of SV extracts.

Figure 7.

Active compounds-targets network relationship diagram.

To further elucidate the key pathways involved in the anti-breast cancer activity, we imported the first 33 key compounds, 144 core targets, and the initial 67 enrichment pathways for SV into Cytoscape 3.9.0 software to construct a comprehensive compound-target-pathway network (Figure 8). The resulting graph comprises of 242 nodes and 1172 edges. Analysis of degree values indicated that several pathways are crucial, including pathways in cancer, neuroactive ligand-receptor interaction, chemical carcinogenesis-receptor activation, Ras signaling pathway, microRNAs in cancer, lipid and atherosclerosis metabolism, calcium signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway AGE-RAGE signaling pathway in diabetic complications proteoglycans in cancer coronavirus disease-COVID-19 hepatitis B transcriptional misregulation in cancer human T-cell leukemia virus 1 infection IL-17 signaling pathway breast cancer Rap1 signaling pathway human cytomegalovirus infection non-small cell lung cancer. These findings demonstrate that the fruting body of SV exerts its therapeutic effects against breast cancer through multiple components acting on multiple targets via various interconnected pathways.

Figure 8.

Active compound-target-pathway network relationship diagram.

GO and KEGG Enrichment Analysis

GO and KEGG pathway enrichment analyses were further performed to indicate the biological activity and possible mechanisms of the potential targets. The GO enrichment analysis of the central nodes produced 222 enriched GO terms (FDR < 0.05), including 134 biological processes, 34 cellular components, and 54 molecular functions. The top 15 enriched GO terms were shown in Figure 9. In detail, the top three terms in the GO biological processes were positive regulation of transcription from RNA polymerase II promoter (GO: 0045944), negative regulation of transcription from RNA polymerase II promoter (GO: 0000122), positive regulation of transcription, DNA-templated (GO: 0045893). According to the GO cell components, the terms included plasma membrane (GO: 0005886), cytoplasm (GO: 0005737), integral component of membrane (GO:0016021). The cell membrane was an essential organelle that regulated the cell signaling and controlled the nutrient transport of the cell. In terms of GO molecular functions, they were mainly enriched in identical protein binding (GO:0042802), zinc ion binding (GO:0008270), calcium ion binding (GO: 0005509).

Figure 9.

Go analysis of potential targets of active compounds. Top 15 enriched GO terms for biological processes, molecular functions, and cellular components.

KEGG pathway enrichment analysis was conducted to further explore the possible functions of the targets (FDR < 0.05), and 67 pathways were obtained. The top 10 signaling pathways with the most number of enrichment targets were pathways in cancer (hsa05200), neuroactive ligand-receptor interaction (hsa04080), chemical carcinogenesis-receptor activation (hsa05207), Ras signaling pathway (hsa04014), microRNAs in cancer (hsa05206), lipid and atherosclerosis (hsa05417), calcium signaling pathway (hsa04020), MAPK signaling pathway (hsa04010), PI3K-Akt signaling pathway (hsa04151), as well as AGE-RAGE signaling pathway in diabetic complications (hsa04933) (Figure 10). These results indicated that the active ingredients of SV regulate multiple signaling pathways, and that signaling pathways such as MAPK and PI3K-Akt may be responsible for SV-induced growth inhibition in breast cancer cells.

Figure 10.

KEGG pathway enrichment analysis of potential targets of active compounds. Top 30 enriched KEGG terms.

Molecular Docking of Compounds to Hub Targets

To further validate the binding affinity between the active compounds and the key targets, molecular docking was conducted using AutoDock Tools 1.5.7 with six key compounds and eight core targets. The calculated binding free energies are presented in Table 2. The three-dimensional topological structures of the compound-target binding models were constructed, as illustrated in Figure 11. Notably, a negative binding energy indicates spontaneous binding of ligand molecules to receptor proteins. When the docking binding energy fell below the empirical threshold (−5.0 kcal/mol), it indicated stronger binding ability between the compound and target.²⁸ Results revealed that phellibaumin B (SV16), naringenin (SV26), hesperetin (SV27), sterubin (SV28), phelligrin A (SV31) and phelligrin C (SV36) could bind to multiple sites on MMP9 (PDB ID: 1GKC), JUN(PDB ID: 5T01), EGF(PDB ID: 1JL9), CCND1(PDB ID: 2W96), IL6(PDB ID: 1ALU), ESR1(PDB ID:4XI3), FOS(PDB ID:1FOS) and EGFR(PDBID : 1XKK) proteins with negative free energy values, indicating relatively higher affinity towards MMP9, EGF, and EGFR compared to other targets based on their respective binding energies. Moreover, one compound exhibited multi-target interactions suggesting its potential for promoting anti-breast cancer effects through multiple pathways.

Figure 11.

Molecular docking of active components and key target proteins in breast cancer. (A) MMP9-SV31, (B) EGF-SV16, (C) EGF-SV26, (D) EGF-SV27, (E) EGF-SV28, (F) EGF-SV36, (G) CCND1-SV28, (H) EGFR-SV16, (I) EGFR-SV26, (J) EGFR-SV27, (K) EGFR-SV31, (L) EGFR-SV36.

Table 2.

Molecular Docking Results of the Core Antitumor Components of S. vaninii With Key Targets.

Compound	Binding energy (kcal/mol)
Compound	MMP9	JUN	EGF	CCND1	IL6	ESR1	FOS	EGFR
SV16	−2.77	−2.25	−4.13	−2.56	−2.43	−2.18	−2.18	−3.54
SV26	−3.85	−2.98	−5.12	−3.79	−4.12	−3.32	−2.37	−4.93
SV27	−3.91	−2.96	−5.94	−2.72	−2.58	−2.78	−2.55	−4.14
SV28	−3.63	−2.58	−4.84	−4.15	−3.37	−2.68	−2.29	−2.98
SV31	−4.68	−0.87	−4.36	−3.00	−3.25	−2.50	−1.49	−5.33
SV36	−2.43	−0.05	−3.43	−2.42	−2.35	−2.57	−1.21	−4.19

Discussion

BRCA is a complex health issue with intricate pathogenesis, a distinct lack of effective therapeutic options, and increasing morbidity. S. vaninii, a traditional medicinal mushroom used for treating tumor-related diseases, contains numerous active compounds with diverse physicochemical properties. In this work, we employed UPLC-Q-TOF/MS and network pharmacology to investigate the active compounds and mechanisms of SV in BRCA treatment. SV was considered to contain multiple compounds with different target proteins. Among these key components, phellibaumin B is a derivative of hispidin with a pyranobenzopyran moiety which has been reported by Wu et al to exhibit NF-κB inhibitory activity with IC₅₀ value of 41.40 μM. NF-κB belongs to the nuclear factor-kappa B family and is known as critical regulators of mammalian immune and inflammatory responses for almost two decades.²¹ Naringenin, hesperetin, sterubin, phelligrins C, phelligrin A are flavanone group polyphenols that possess significant pharmacological properties including anti-inflammatory, antioxidant neuroprotective hepatoprotective activities as well as anticancer effects. Naringenin exerts its anticancer effects through multiple mechanisms, including induction of apoptosis, cell cycle arrest, inhibition of angiogenesis, and modification of several signaling pathways, including the Wnt/β-catenin, PI3 K/Akt, NF-ĸB, and TGF-β pathways.²⁹ Hesperetin can inhibit cell proliferation, migration and BRCA stem cells, as well as induce apoptosis and cell cycle arrest in vitro. It can also inhibit tumor growth, metastasis and neoplastic changes in tissue architecture in vivo. These chemotherapeutic and chemosensitizing activities of hesperetin have been attributed to multiple mechanisms, including modulation of signaling pathways, glucose uptake, enzymes, miRNA expression, oxidative status, cell cycle regulatory proteins, tumor suppressor p53, plasma and liver lipid profiles, and DNA repair mechanisms.³⁰ Wu et al reported that the benzyl dihydroflavone phelligrin A plays an important role in blocking both LPS-induced and constitutive NF-κB activity in human prostate cancer cells. NF-κB-regulated genes are involved in tumor cell proliferation and metastasis, and inhibition of NF-κB signaling may be an attractive antitumor approach.²¹ Phelligrin C is a new active ingredient with a structure similar to that of phelligrin A, except for the addition of 1 molecule o-hydroxytoluene. Molecular docking results showed that the binding ability of phelligrin C to the key targets EGF/EGFR was stronger. Epidermal growth factor (EGF) is a well-known growth factor that induces cancer cell migration and invasion. The EGF receptor (EGFR) and its stimulation by EGF have been implicated in a number of cell proliferative disorders or malignancies. EGFR dimerization and tyrosine autophosphorylation can activate several intracellular signaling pathways, such as PI3 K/AKT signaling pathway, JUK signaling pathway. These pathways play an important role in cell growth and proliferation.³¹

PPI network analysis and KEGG enrichment revealed that the therapeutic mechanism of SV is closely related to the targets MMP9, JUN, EGF, CCND1, IL6, ESR1, FOS, and EGFR. Matrix metalloproteinase 9 (MMP9) is an enzyme that plays an important role in the first step of metastasis by degrading the extracellular matrix.³² c-JUN is a prominent component of many AP-1 complexes and plays a critical role in the phenotype, tumorigenesis and metastasis of BRCA cells.³³ Down-regulation of IL6 expression inhibits blood vessel formation and has an immunomodulatory effect against breast cancer.³⁴ Acquisition of ligand-independent ESR1 mutations during aromatase inhibitor therapy in metastatic estrogen receptor (ER)-positive breast cancer is a common mechanism of resistance to hormone therapy. Preclinical and clinical studies have shown that ESR1 mutations can be pre-existing in primary tumors and enriched during metastasis. ESR1 mutations express a unique transcriptional profile that favors tumor progression, suggesting that selected ESR1 mutations may influence metastasis.³⁵

This study provides a preliminary revelation of the active ingredients and potential pharmacological mechanisms of SV in the treatment of breast cancer. These findings establish a vital theoretical basis and serve as a scientific reference for the future investigating the pharmacological mechanisms of SV. However, this approach is an in vitro predictive technology that lacks the ability to provide dose–response relationships, which affects the accuracy of network analysis. Therefore, their efficacy against breast cancer was further investigated in vivo and in vitro.

Conclusions

In this paper, UPLC-Q-TOF/MS technology was utilized for rapid qualitative analysis of the chemical composition of S. vaninii. As a result, 53 compounds were effectively separated and identified, including one novel compound. Thirty-three active ingredients and 144 common targets were then employed to investigate the potential mechanism by which SV exerts its effects against BRCA. The results indicated that six compounds including phellibaumin B, naringenin, hesperetin, sterubin, phelligrin A, and phelligrin C might be the core active ingredients of SV able to exert therapeutic effects against breast cancer. and the molecular mechanism may be related to targeting Ras, MAPK, PI3K-Akt, and other signal pathways associated with the key targets MMP9, EGF, and EGFR. These findings highlight the multifaceted nature of traditional Chinese fungal medicines characterized by their multi-component, multi-target, and multi-pathway properties.

Materials and Methods

Chemical Composition Analysis

Reagents and Materials

The MS-grade methanol and water were procured from Thermo Fisher Scientific Co., Ltd (Handan, China). The MS-grade formic acid was obtained from Beijing Chemical Plant (Beijing, China). For sample extraction, ethanol and water of analytical purity were used.

The wild fruiting body of S. vaninii was collected from Changbai Mountain, Jilin Province, China, and authenticated by Prof. Tolgor. A voucher specimen (No. 20220910) has been deposited at the Institute of Edible Fungi, Handan University, Handan, China.

Preparation of Sample Solution

The air-dried powdered fruiting body of SV (50 g) was subjected to ultrasonic extraction for 90 min at 45°C using 500 mL of an aqueous ethanol solution with a concentration of 80% (v/v). After centrifugation at 6000 rpm for 15 min, the supernatant was evaporated under reduced pressure at a temperature of 40 °C, and then transferred to a clean lyophilization bottle for drying purposes. The dried extracts were reconstituted with methanol and filtered through a filter with a pore size of 0.22 µm, then 10 µL of the filtrate was injected into the UPLC system for analysis.

UPLC-Q-TOF/MS Analysis

The chromatographic separation was conducted using a Waters Acquity UPLC system, which was equipped with a binary solvent system, an autosampler, and a photodiode array (PDA) detector. A temperature of 40 °C was maintained during the analysis using an Acquity UPLC BEH C18 column (2.1 mm x 150 mm, 1.7 μm, Waters, Manchester, UK). The mobile phase consisted of methanol (A) and 0.1% formic acid (Fa) in water (B), and a gradient elution procedure was employed. The following mobile phase gradient protocol was selected: 0–2 min: 5% A; 2–50 min: 5–100% A; 50–55 min: 100% A; 50–55.1 min: 100–5% A; and finally from minute 55.1 to minute 60: 5%A. Flow rate used for the analysis was set at 0.3 mL/min with an injection volume of 10 μL.

To couple the Acquity UPLC system with mass spectrometry detection, a hybrid quadrupole orthogonal time-of-flight (G2Qtof) mass spectrometer equipped with electrospray ionization (ESI) was utilized. The operating parameters were as follows: capillary voltage = 2.8 kV, sampling cone = 30 eV, extraction cone = 1.0 eV, source temperature = 100°C, desolvation temperature = 300°C, cone gas flow (N2) = 50 L/h, and desolvation gas flow (N2) = 900 L/h. The mass scan range covered m/z values from 50 to1200 Da.

Mechanism Study by Network Pharmacology

Prediction of Active Compound Targets

All polyphenols identified through screening by UPLC mass spectra were converted into canonical SMILES formats, and their potential targets were obtained from the TCMSP (https://tcmspw.com/tcmsp.php) and Swiss Target Prediction (http:// www.swisstargetprediction.ch/) databases based on the condition that probability >0.

Searching for BRCA Targets

BRCA-associated target genes were collected from the TCGA database, and RNA-Seq data from the 1185 breast cancer (BRCA) tissue samples were analyzed, including 1086 primary tumor samples and 99 normal solid tissue samples. In terms of analysis used DESeq2 data package, BRCA-related significantly differential expression genes exhibited the following characteristics: FDR < 0.05 and |log2(fold change)| > 1. Duplicate data and false-positive genes were then deleted.

Networks Construction

The SV and BRCA protein–protein interaction (PPI) networks were merged using the STRING database version 11.0 (https://string-db.org). The unconnected nodes in the network were hidden. A compound-target network and a compound-target-pathway network were constructed using Cytoscape 3.9.0 software. The compounds, targets, and pathways were described by nodes and the interaction was encoded by edges.

Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Enrichment Analysis

GO and KEGG enrichment analyses were used to further clarify the biological interpretations of the hub genes of the network. The GO analysis included three aspects: biological process (BP), molecular function (MF) and cellular component (CC). GO terms and pathways with FDR < 0.05 were selected. In addition, a KEGG pathway network was constructed using Cytoscape version 3.9.0 software.

Molecular Docking

The 3D structures of the active compounds associated with the targets were retrieved from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/). The 3D structures of the target proteins were obtained from the Protein Data Bank (PDB) database (http://www.rcsb.org/). The ligand-receptor complex structures were selected and modified by removing the original ligands. The 3D structures of the ligand-receptor complexes were visualized using PyMol software. Finally, for validation of molecular docking, the preprocessed proteins and compositions were imported into Autodock Tools 1.5.7. Upon completion of all docking simulations, interactions between all active molecules and disease targets were ranked based on their strength.

Statistical Analysis

Mass spectrometry data were analyzed using Mass Lynx V4.1 software, and the structure of the compounds was predicted using the Chemspider, PubChem, and Lipidomics Gateway databases.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical Approval

Ethical approval is not applicable for this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The work was supported by Hebei Natural Science Foundation, China (grant number C2019109043), the project of Handan University (grant number ZZ2023002) and the Funded by Science and Technology Project of Hebei Education Department (grant number ZC2023191).

ORCID iD

Li-feng Zan

Statement of Human and Animal Rights

This article does not contain any studies with human or animal subjects.

Statement of Informed Consent

There are no human subjects in this article and informed consent is not applicable.

Trial Registration

Not applicable, because this article does not contain any clinical trials.

Supplemental Material

Supplemental material for this article is available online.

Notes

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Qualitative Analysis Using UPLC-Q-TOF/MS and a Systematic Network Pharmacology-Based Strategy to Investigate the Active Constituents and Potential Mechanisms Against Breast Cancer in the Fruit Body of Sanghuangporus vaninii

Abstract

Keywords

Introduction

Results

Chemical Composition

Target Identifying and Prediction

Breast Cancer Differentially Expressed Genes (BRCAdegs) Search

Network Construction and Analysis

GO and KEGG Enrichment Analysis

Molecular Docking of Compounds to Hub Targets

Discussion

Conclusions

Materials and Methods

Chemical Composition Analysis

Reagents and Materials

Preparation of Sample Solution

UPLC-Q-TOF/MS Analysis

Mechanism Study by Network Pharmacology

Prediction of Active Compound Targets

Searching for BRCA Targets

Networks Construction

Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Enrichment Analysis

Molecular Docking

Statistical Analysis

Footnotes

Declaration of Conflicting Interests

Ethical Approval

Funding

ORCID iD

Statement of Human and Animal Rights

Statement of Informed Consent

Trial Registration

Supplemental Material

Notes

References