Advances in fundamental and translational breast cancer research in 2022

doi:10.19401/j.cnki.1007-3639.2023.02.001

Abstract

Abstract:

According to the data released by the International Cancer Research Institute of the World Health Organization (WHO), breast cancer is the malignant tumor with the highest incidence rate in women, and seriously endangers women's health.Many impressive advances have been achieved in fundamental and translational research of breast cancer, which deepened the understanding of the molecular nature of breast cancer and provided new scientific strategies for the precision treatment of breast cancer. This paper summarized the annual advances in fundamental and translational breast cancer research in 2022 in seven sections: tumor metabolism, tumor microenvironment, microbes and tumors, tumor metastasis, tumor drug resistance and drug screening, multi-omics research and artificial intelligence. Furthermore, we proposed an outlook on the future directions of breast cancer research to provide a reference for future studies.

Key words: Breast cancer, Fundamental and translational research, Research advances

CLC Number:

R737.9

WANG Ziyu, XIAO Yi, JIANG Yizhou, SHAO Zhimin. Advances in fundamental and translational breast cancer research in 2022[J]. China Oncology, 2023, 33(2): 95-102.

References 71

[1]	SUNG H, FERLAY J, SIEGEL R L, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2021, 71(3): 209-249. doi: 10.3322/caac.v71.3
[2]	JIANG H M, WEI H M, WANG H, et al. Zeb1-induced metabolic reprogramming of glycolysis is essential for macrophage polarization in breast cancer[J]. Cell Death Dis, 2022, 13(3): 206. doi: 10.1038/s41419-022-04632-z pmid: 35246504
[3]	ZHU W J, CHEN X, GUO X Y, et al. Low glucose-induced overexpression of HOXC-AS3 promotes metabolic reprogramming of breast cancer[J]. Cancer Res, 2022, 82(5): 805-818. doi: 10.1158/0008-5472.CAN-21-1179 pmid: 35031573
[4]	CHEN X M, LUO R, ZHANG Y M, et al. Long noncoding RNA DIO3OS induces glycolytic-dominant metabolic reprogramming to promote aromatase inhibitor resistance in breast cancer[J]. Nat Commun, 2022, 13(1): 7160. doi: 10.1038/s41467-022-34702-x pmid: 36418319
[5]	PARIDA P K, MARQUEZ-PALENCIA M, NAIR V, et al. Metabolic diversity within breast cancer brain-tropic cells determines metastatic fitness[J]. Cell Metab, 2022, 34(1): 90-105.e7. doi: 10.1016/j.cmet.2021.12.001 pmid: 34986341
[6]	GOMES A P, ILTER D, LOW V, et al. Altered propionate metabolism contributes to tumour progression and aggressiveness[J]. Nat Metab, 2022, 4(4): 435-443. doi: 10.1038/s42255-022-00553-5 pmid: 35361954
[7]	GONG Z, LI Q, SHI J Y, et al. Lipid-laden lung mesenchymal cells foster breast cancer metastasis via metabolic reprogramming of tumor cells and natural killer cells[J]. Cell Metab, 2022, 34(12): 1960-1976.e9. doi: 10.1016/j.cmet.2022.11.003 pmid: 36476935
[8]	DIXON S J, LEMBERG K M, LAMPRECHT M R, et al. Ferroptosis: an iron-dependent form of nonapoptotic cell death[J]. Cell, 2012, 149(5): 1060-1072. doi: 10.1016/j.cell.2012.03.042 pmid: 22632970
[9]	TANG D L, CHEN X, KANG R, et al. Ferroptosis: molecular mechanisms and health implications[J]. Cell Res, 2021, 31(2): 107-125. doi: 10.1038/s41422-020-00441-1 pmid: 33268902
[10]	LI H Y, YANG P H, WANG J H, et al. HLF regulates ferroptosis, development and chemoresistance of triple-negative breast cancer by activating tumor cell-macrophage crosstalk[J]. J Hematol Oncol, 2022, 15(1): 2. doi: 10.1186/s13045-021-01223-x
[11]	WU M M, ZHANG X, ZHANG W J, et al. Cancer stem cell regulated phenotypic plasticity protects metastasized cancer cells from ferroptosis[J]. Nat Commun, 2022, 13(1): 1371. doi: 10.1038/s41467-022-29018-9 pmid: 35296660
[12]	ZOU Y T, ZHENG S Q, XIE X H, et al. N6-methyladenosine regulated FGFR4 attenuates ferroptotic cell death in recalcitrant HER2-positive breast cancer[J]. Nat Commun, 2022, 13(1): 2672. doi: 10.1038/s41467-022-30217-7 pmid: 35562334
[13]	YANG F, XIAO Y, DING J H, et al. Ferroptosis heterogeneity in triple-negative breast cancer reveals an innovative immunotherapy combination strategy[J]. Cell Metab, 2023, 35(1): 84-100.e8. doi: 10.1016/j.cmet.2022.09.021
[14]	ZHANG H L, HU B X, LI Z L, et al. PKCβⅡ phosphorylates ACSL4 to amplify lipid peroxidation to induce ferroptosis[J]. Nat Cell Biol, 2022, 24(1): 88-98. doi: 10.1038/s41556-021-00818-3
[15]	XIE Y Z, WANG B Y, ZHAO Y N, et al. Mammary adipocytes protect triple-negative breast cancer cells from ferroptosis[J]. J Hematol Oncol, 2022, 15(1): 72. doi: 10.1186/s13045-022-01297-1
[16]	LI K, LIN C C, LI M H, et al. Multienzyme-like reactivity cooperatively impairs glutathione peroxidase 4 and ferroptosis suppressor protein 1 pathways in triple-negative breast cancer for sensitized ferroptosis therapy[J]. ACS Nano, 2022, 16(2): 2381-2398. doi: 10.1021/acsnano.1c08664 pmid: 35041395
[17]	YANG J, JIA Z G, ZHANG J, et al. Metabolic intervention nanoparticles for triple-negative breast cancer therapy via overcoming FSP1-mediated ferroptosis resistance[J]. Adv Healthc Mater, 2022, 11(13): e2102799.
[18]	PAN W L, TAN Y, MENG W, et al. Microenvironment-driven sequential ferroptosis, photodynamic therapy, and chemotherapy for targeted breast cancer therapy by a cancer-cell-membrane-coated nanoscale metal-organic framework[J]. Biomaterials, 2022, 283: 121449. doi: 10.1016/j.biomaterials.2022.121449
[19]	ZHOU A W, FANG T L, CHEN K R, et al. Biomimetic activator of sonodynamic ferroptosis amplifies inherent peroxidation for improving the treatment of breast cancer[J]. Small, 2022, 18(12): e2106568.
[20]	SEUNG E, XING Z, WU L, et al. A trispecific antibody targeting HER2 and T cells inhibits breast cancer growth via CD4 cells[J]. Nature, 2022, 603(7900): 328-334. doi: 10.1038/s41586-022-04439-0
[21]	NALIO RAMOS R, MISSOLO-KOUSSOU Y, GERBER-FERDER Y, et al. Tissue-resident FOLR2⁺ macrophages associate with CD8⁺ T cell infiltration in human breast cancer[J]. Cell, 2022, 185(7): 1189-1207.e25. doi: 10.1016/j.cell.2022.02.021
[22]	NIXON B G, KUO F S, JI L L, et al. Tumor-associated macrophages expressing the transcription factor IRF8 promote T cell exhaustion in cancer[J]. Immunity, 2022, 55(11): 2044-2058.e5. doi: 10.1016/j.immuni.2022.10.002
[23]	BLOMBERG O S, SPAGNUOLO L, GARNER H, et al. IL-5-producing CD4⁺ T cells and eosinophils cooperate to enhance response to immune checkpoint blockade in breast cancer[J]. Cancer Cell, 2023, 41(1): 106-123.e10. doi: 10.1016/j.ccell.2022.11.014
[24]	KAY E J, PATERSON K, RIERA-DOMINGO C, et al. Cancer-associated fibroblasts require proline synthesis by PYCR1 for the deposition of pro-tumorigenic extracellular matrix[J]. Nat Metab, 2022, 4(6): 693-710. doi: 10.1038/s42255-022-00582-0 pmid: 35760868
[25]	PAPANICOLAOU M, PARKER A L, YAM M, et al. Temporal profiling of the breast tumour microenvironment reveals collagen Ⅻ as a driver of metastasis[J]. Nat Commun, 2022, 13(1): 4587. doi: 10.1038/s41467-022-32255-7
[26]	HONGU T, PEIN M, INSUA-RODRÍGUEZ J, et al. Perivascular tenascin C triggers sequential activation of macrophages and endothelial cells to generate a pro-metastatic vascular niche in the lungs[J]. Nat Cancer, 2022, 3(4): 486-504. doi: 10.1038/s43018-022-00353-6
[27]	ZHU Q Z, ZHU Y, HEPLER C, et al. Adipocyte mesenchymal transition contributes to mammary tumor progression[J]. Cell Rep, 2022, 40(11): 111362. doi: 10.1016/j.celrep.2022.111362
[28]	WANG Y Q, XIE H L, WU Y, et al. Bioinspired lipoproteins of furoxans-oxaliplatin remodel physical barriers in tumor to potentiate T-cell infiltration[J]. Adv Mater, 2022, 34(14): e2110614.
[29]	NIA H T, MUNN L L, JAIN R K. Physical traits of cancer[J]. Science, 2020, 370(6516): eaaz0868. doi: 10.1126/science.aaz0868
[30]	BERA K, KIEPAS A, GODET I, et al. Extracellular fluid viscosity enhances cell migration and cancer dissemination[J]. Nature, 2022, 611(7935): 365-373. doi: 10.1038/s41586-022-05394-6
[31]	ROMANI P, NIRCHIO N, ARBOIT M, et al. Mitochondrial fission links ECM mechanotransduction to metabolic redox homeostasis and metastatic chemotherapy resistance[J]. Nat Cell Biol, 2022, 24(2): 168-180. doi: 10.1038/s41556-022-00843-w pmid: 35165418
[32]	HANAHAN D. Hallmarks of cancer: new dimensions[J]. Cancer Discov, 2022, 12(1): 31-46. doi: 10.1158/2159-8290.CD-21-1059 pmid: 35022204
[33]	HIEKEN T J, CHEN J, HOSKIN T L, et al. The microbiome of aseptically collected human breast tissue in benign and malignant disease[J]. Sci Rep, 2016, 6: 30751. doi: 10.1038/srep30751 pmid: 27485780
[34]	NEJMAN D, LIVYATAN I, FUKS G, et al. The human tumor microbiome is composed of tumor type-specific intracellular bacteria[J]. Science, 2020, 368(6494): 973-980. doi: 10.1126/science.aay9189 pmid: 32467386
[35]	WANG H, RONG X Y, ZHAO G, et al. The microbial metabolite trimethylamine N-oxide promotes antitumor immunity in triple-negative breast cancer[J]. Cell Metab, 2022, 34(4): 581-594.e8. doi: 10.1016/j.cmet.2022.02.010 pmid: 35278352
[36]	FU A K, YAO B Q, DONG T T, et al. Tumor-resident intracellular microbiota promotes metastatic colonization in breast cancer[J]. Cell, 2022, 185(8): 1356-1372.e26. doi: 10.1016/j.cell.2022.02.027 pmid: 35395179
[37]	DENG H, MUTHUPALANI S, ERDMAN S, et al. Translocation of helicobacter hepaticus synergizes with myeloid-derived suppressor cells and contributes to breast carcinogenesis[J]. Oncoimmunology, 2022, 11(1): 2057399. doi: 10.1080/2162402X.2022.2057399
[38]	NARUNSKY-HAZIZA L, SEPICH-POORE G D, LIVYATAN I, et al. Pan-cancer analyses reveal cancer-type-specific fungal ecologies and bacteriome interactions[J]. Cell, 2022, 185(20): 3789-3806.e17. doi: 10.1016/j.cell.2022.09.005
[39]	DOHLMAN A B, KLUG J, MESKO M, et al. A pan-cancer mycobiome analysis reveals fungal involvement in gastrointestinal and lung tumors[J]. Cell, 2022, 185(20): 3807-3822.e12. doi: 10.1016/j.cell.2022.09.015 pmid: 36179671
[40]	XIAO S S, SHI H, ZHANG Y, et al. Bacteria-driven hypoxia targeting delivery of chemotherapeutic drug proving outcome of breast cancer[J]. J Nanobiotechnol, 2022, 20(1): 178. doi: 10.1186/s12951-022-01373-1 pmid: 35366890
[41]	NGUYEN B, FONG C, LUTHRA A, et al. Genomic characterization of metastatic patterns from prospective clinical sequencing of 25, 000 patients[J]. Cell, 2022, 185(3): 563-575.e11. doi: 10.1016/j.cell.2022.01.003
[42]	GARCIA-RECIO S, HINOUE T, WHEELER G L, et al. Multiomics in primary and metastatic breast tumors from the AURORA US network finds microenvironment and epigenetic drivers of metastasis[J]. Nat Cancer, 2022[Epub ahead of print].
[43]	GONG Z, LI Q, SHI J Y, et al. Lung fibroblasts facilitate pre-metastatic niche formation by remodeling the local immune microenvironment[J]. Immunity, 2022, 55(8): 1483-1500.e9. doi: 10.1016/j.immuni.2022.07.001 pmid: 35908547
[44]	QI M Y, XIA Y, WU Y J, et al. Lin28B-high breast cancer cells promote immune suppression in the lung pre-metastatic niche via exosomes and support cancer progression[J]. Nat Commun, 2022, 13(1): 897. doi: 10.1038/s41467-022-28438-x pmid: 35173168
[45]	GUTWILLIG A, SANTANA-MAGAL N, FARHAT-YOUNIS L, et al. Transient cell-in-cell formation underlies tumor relapse and resistance to immunotherapy[J]. Elife, 2022, 11: e80315. doi: 10.7554/eLife.80315
[46]	BALDOMINOS P, BARBERA-MOURELLE A, BARREIRO O, et al. Quiescent cancer cells resist T cell attack by forming an immunosuppressive niche[J]. Cell, 2022, 185(10): 1694-1708.e19. doi: 10.1016/j.cell.2022.03.033
[47]	CHANG C A, JEN J, JIANG S W, et al. Ontogeny and vulnerabilities of drug-tolerant persisters in HER2⁺ breast cancer[J]. Cancer Discov, 2022, 12(4): 1022-1045. doi: 10.1158/2159-8290.CD-20-1265
[48]	MARSOLIER J, PROMPSY P, DURAND A, et al. H3K27me3 conditions chemotolerance in triple-negative breast cancer[J]. Nat Genet, 2022, 54(4): 459-468. doi: 10.1038/s41588-022-01047-6 pmid: 35410383
[49]	LIU X W, LU Y W, HUANG J Y, et al. CD16⁺ fibroblasts foster a trastuzumab-refractory microenvironment that is reversed by VAV2 inhibition[J]. Cancer Cell, 2022, 40(11): 1341-1357.e13. doi: 10.1016/j.ccell.2022.10.015
[50]	LI H Z, XIAO Y, LI Q, et al. The allergy mediator histamine confers resistance to immunotherapy in cancer patients via activation of the macrophage histamine receptor H1[J]. Cancer Cell, 2022, 40(1): 36-52.e9. doi: 10.1016/j.ccell.2021.11.002
[51]	MA S J, ZHAO Y, LEE W C, et al. Hypoxia induces HIF1α-dependent epigenetic vulnerability in triple-negative breast cancer to confer immune effector dysfunction and resistance to anti-PD-1 immunotherapy[J]. Nat Commun, 2022, 13(1): 4118. doi: 10.1038/s41467-022-31764-9
[52]	JAAKS P, COKER E A, VIS D J, et al. Effective drug combinations in breast, colon and pancreatic cancer cells[J]. Nature, 2022, 603(7899): 166-173. doi: 10.1038/s41586-022-04437-2
[53]	GUILLEN K P, FUJITA M, BUTTERFIELD A J, et al. A human breast cancer-derived xenograft and organoid platform for drug discovery and precision oncology[J]. Nat Cancer, 2022, 3(2): 232-250. doi: 10.1038/s43018-022-00337-6
[54]	JIANG Y Z, MA D, SUO C, et al. Genomic and transcriptomic landscape of triple-negative breast cancers: subtypes and treatment strategies[J]. Cancer Cell, 2019, 35(3): 428-440.e5. doi: 10.1016/j.ccell.2019.02.001
[55]	BERTUCCI F, NG C K Y, PATSOURIS A, et al. Genomic characterization of metastatic breast cancers[J]. Nature, 2019, 569(7757): 560-564. doi: 10.1038/s41586-019-1056-z
[56]	MERTINS P, MANI D R, RUGGLES K V, et al. Proteogenomics connects somatic mutations to signalling in breast cancer[J]. Nature, 2016, 534(7605): 55-62. doi: 10.1038/nature18003
[57]	CURTIS C, SHAH S P, CHIN S F, et al. The genomic and transcriptomic architecture of 2 000 breast tumours reveals novel subgroups[J]. Nature, 2012, 486(7403): 346-352. doi: 10.1038/nature10983
[58]	PEREIRA B, CHIN S F, RUEDA O M, et al. Erratum: the somatic mutation profiles of 2, 433 breast cancers refine their genomic and transcriptomic landscapes[J]. Nat Commun, 2016, 7: 11908. doi: 10.1038/ncomms11908
[59]	BARECHE Y, VENET D, IGNATIADIS M, et al. Unravelling triple-negative breast cancer molecular heterogeneity using an integrative multiomic analysis[J]. Ann Oncol, 2018, 29(4): 895-902. doi: S0923-7534(19)45470-7 pmid: 29365031
[60]	XIAO Y, MA D, YANG Y S, et al. Comprehensive metabolomics expands precision medicine for triple-negative breast cancer[J]. Cell Res, 2022, 32(5): 477-490. doi: 10.1038/s41422-022-00614-0 pmid: 35105939
[61]	JIANG L, YOU C, XIAO Y, et al. Radiogenomic analysis reveals tumor heterogeneity of triple-negative breast cancer[J]. Cell Rep Med, 2022, 3(7): 100694.
[62]	LOMAKIN A, SVEDLUND J, STRELL C, et al. Spatial genomics maps the structure, nature and evolution of cancer clones[J]. Nature, 2022, 611(7936): 594-602. doi: 10.1038/s41586-022-05425-2
[63]	FUNNELL T, O'FLANAGAN C H, WILLIAMS M J, et al. Single-cell genomic variation induced by mutational processes in cancer[J]. Nature, 2022, 612(7938): 106-115. doi: 10.1038/s41586-022-05249-0
[64]	MARTINI R, DELPE P, CHU T R, et al. African ancestry-associated gene expression profiles in triple-negative breast cancer underlie altered tumor biology and clinical outcome in women of African descent[J]. Cancer Discov, 2022, 12(11): 2530-2551. doi: 10.1158/2159-8290.CD-22-0138
[65]	STRAND S H, RIVERO-GUTIÉRREZ B, HOULAHAN K E, et al. Molecular classification and biomarkers of clinical outcome in breast ductal carcinoma in situ: analysis of TBCRC 038 and RAHBT cohorts[J]. Cancer Cell, 2022, 40(12): 1521-1536.e7. doi: 10.1016/j.ccell.2022.10.021
[66]	LIPS E H, KUMAR T, MEGALIOS A, et al. Genomic analysis defines clonal relationships of ductal carcinoma in situ and recurrent invasive breast cancer[J]. Nat Genet, 2022, 54(6): 850-860. doi: 10.1038/s41588-022-01082-3
[67]	RISOM T, GLASS D R, AVERBUKH I, et al. Transition to invasive breast cancer is associated with progressive changes in the structure and composition of tumor stroma[J]. Cell, 2022, 185(2): 299-310.e18. doi: 10.1016/j.cell.2021.12.023 pmid: 35063072
[68]	YALA A, MIKHAEL P G, LEHMAN C, et al. Optimizing risk-based breast cancer screening policies with reinforcement learning[J]. Nat Med, 2022, 28(1): 136-143. doi: 10.1038/s41591-021-01599-w pmid: 35027757
[69]	WANG Y, ACS B, ROBERTSON S, et al. Improved breast cancer histological grading using deep learning[J]. Ann Oncol, 2022, 33(1): 89-98. doi: 10.1016/j.annonc.2021.09.007
[70]	SAMMUT S J, CRISPIN-ORTUZAR M, CHIN S F, et al. Multi-omic machine learning predictor of breast cancer therapy response[J]. Nature, 2022, 601(7894): 623-629. doi: 10.1038/s41586-021-04278-5
[71]	ZHAO S, YAN C Y, LV H, et al. Deep learning framework for comprehensive molecular and prognostic stratifications of triple-negative breast cancer[J]. Fundam Res, 2022[Epub ahead of print].