Molecular principles of metastasis: a hallmark of cancer revisited

Signal Transduction and Targeted Therapy, Journal Year: 2020, Volume and Issue: 5(1)

Published: March 12, 2020

Abstract Metastasis is the hallmark of cancer that responsible for greatest number cancer-related deaths. Yet, it remains poorly understood. The continuous evolution biology research and emergence new paradigms in study metastasis have revealed some molecular underpinnings this dissemination process. invading tumor cell, on its way to target site, interacts with other proteins cells. Recognition these interactions improved understanding biological principles metastatic cell govern mobility plasticity. Communication microenvironment allows cells overcome stromal challenges, settle, colonize. These characteristics are driven by genetic epigenetic modifications within itself microenvironment. Establishing mechanisms process crucial finding open therapeutic windows successful interventions. In review, authors explore recent advancements field highlight latest insights contribute shaping cancer.

Language: Английский

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Exploring tissue architecture using spatial transcriptomics

Nature, Journal Year: 2021, Volume and Issue: 596(7871), P. 211 - 220

Published: Aug. 11, 2021

Language: Английский

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Eleven grand challenges in single-cell data science

Genome biology, Journal Year: 2020, Volume and Issue: 21(1)

Published: Feb. 7, 2020

Abstract The recent boom in microfluidics and combinatorial indexing strategies, combined with low sequencing costs, has empowered single-cell technology. Thousands—or even millions—of cells analyzed a single experiment amount to data revolution biology pose unique science problems. Here, we outline eleven challenges that will be central bringing this emerging field of forward. For each challenge, highlight motivating research questions, review prior work, formulate open This compendium is for established researchers, newcomers, students alike, highlighting interesting rewarding problems the coming years.

Language: Английский

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A compendium of mutational cancer driver genes

Nature reviews. Cancer, Journal Year: 2020, Volume and Issue: 20(10), P. 555 - 572

Published: Aug. 10, 2020

Language: Английский

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Defining the Hallmarks of Metastasis

Cancer Research, Journal Year: 2019, Volume and Issue: 79(12), P. 3011 - 3027

Published: May 3, 2019

Abstract Metastasis is the primary cause of cancer morbidity and mortality. The process involves a complex interplay between intrinsic tumor cell properties as well interactions cells multiple microenvironments. outcome development nearby or distant discontiguous secondary mass. To successfully disseminate, metastatic acquire in addition to those necessary become neoplastic. Heterogeneity mechanisms involved, routes dissemination, redundancy molecular pathways that can be utilized, ability piggyback on actions surrounding stromal makes defining hallmarks metastasis extraordinarily challenging. Nonetheless, this review identifies four distinguishing features are required: motility invasion, modulate site local microenvironments, plasticity, colonize tissues. By these first principles metastasis, we provide means for focusing efforts aspects will improve patient outcomes.

Language: Английский

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Macrophage diversity in cancer revisited in the era of single-cell omics

Trends in Immunology, Journal Year: 2022, Volume and Issue: 43(7), P. 546 - 563

Published: June 9, 2022

TAMs have diverse functions in cancer, reflecting the heterogenous nature of these immune cells. Here, we propose a new nomenclature to identify TAM subsets.Recent single cell multi-omics technologies, which allow clustering subsets an unbiased manner, significantly advanced our understanding molecular diversity mice and humans.Novel mechanisms potential therapeutic targets been identified that might regulate tumor-promoting function different subsets.TAM opens promising opportunities for envisaging putative cancer treatments. Tumor-associated macrophages (TAMs) multiple potent and, thus, represent important targets. These highlight TAMs. Recent omics technologies However, unifying annotation their signatures is lacking. review recent major studies transcriptome, epigenome, metabolome, spatial with specific focus on We also consensus model present avenues future research. one most abundant types tumors [1.Cassetta L. Pollard J.W. Targeting macrophages: approaches cancer.Nat. Rev. Drug Discov. 2018; 17: 887-904Crossref PubMed Scopus (650) Google Scholar]. Since initial decade ago [2.Qian B.Z. Macrophage enhances tumor progression metastasis.Cell. 2010; 141: 39-51Abstract Full Text PDF (3151) Scholar], functional now widely appreciated, many seminal field [3.Yang M. et al.Diverse microenvironments.Cancer Res. 78: 5492-5503Crossref (202) Scholar, 4.DeNardo D.G. Ruffell B. Macrophages as regulators tumour immunity immunotherapy.Nat. Immunol. 2019; 19: 369-382Crossref (643) 5.Lopez-Yrigoyen al.Macrophage targeting cancer.Ann. N. Y. Acad. Sci. 2021; 1499: 18-41Crossref (25) This array includes promotion growth, lineage plasticity, invasion, remodeling extracellular matrix, crosstalk endothelial, mesenchymal stromal cells, other cells; effects can result progression, metastasis (see Glossary), therapy resistance [6.Mantovani A. al.Tumour-associated treatment oncology.Nat. Clin. Oncol. 2017; 14: 399-416Crossref (1675) Scholar,7.Guc E. Redefining macrophage neutrophil biology metastatic cascade.Immunity. 54: 885-902Abstract (13) With wide application years seen explosion data illustrating cellular heterogeneity resulting unprecedented amount information TAMs, regardless main studies. Links between are emerging. terminology lacking, making direct comparisons full utilization sets difficult. In this review, summarize human data; include traditional nomenclatures, at levels single-cell transcriptomic, epigenomic, metabolic multi-omics, opportunities, directions. subsets. hope will serve starting point help build complete picture dynamic interactions tumor, well microenvironment (TME). A used describe has now-obsolete M1/M2 model, proposed ~20 ago; it separated into two distinct arms: M1 or 'classically' activated; M2 'alternatively' activated, largely based vitro stimulating type 1 2 cytokines [8.Mills C.D. al.M-1/M-2 Th1/Th2 paradigm.J. 2000; 164: 6166-6173Crossref The newer term 'M1-like' phenotype typically described proinflammatory induced by Toll-like receptor (TLR) ligands cytokines, namely IFN-γ TNF-α. Conversely, 'M2-like' having anti-inflammatory characteristics, being activated interleukin (IL)-4 IL-13, producing TGF-β profibrotic factors. nomenclature, albeit used, remains oversimplified [9.Martinez F.O. Gordon S. paradigm activation: time reassessment.F1000Prime Rep. 2014; 6: 13Crossref (2673) Scholar,10.Nahrendorf Swirski F.K. Abandoning network function.Circ. 2016; 119: 414-417Crossref (195) Indeed, significant morphology, function, surface marker expression observed resident-tissue (RTMs) from organs [11.Bleriot C. al.Determinants resident tissue identity function.Immunity. 2020; 52: 957-970Abstract (94) Scholar]; moreover, co-expression both gene almost all [12.Mulder K. al.Cross-tissue landscape monocytes health disease.Immunity. 1883-1900Abstract Therefore, spectrum polarization relates represents more sensible approach describing [10.Nahrendorf Scholar,13.Mosser D.M. Edwards J.P. Exploring activation.Nat. 2008; 8: 958-969Crossref (5864) normal homeostasis, tightly regulated niche-like local environment, recently [14.Guilliams al.Establishment maintenance niche.Immunity. 434-451Abstract (138) Another layer derives origin. Using lineage-tracing mice, illustrated mouse RTMs derived early erythromyeloid progenitors formed either yolk sac fetal liver [15.Geissmann F. al.Blood consist principal migratory properties.Immunity. 2003; 71-82Abstract (2514) Scholar,16.Gomez Perdiguero al.Tissue-resident originate yolk-sac-derived erythro-myeloid progenitors.Nature. 2015; 518: 547-551Crossref (1236) Additionally, adult may derive circulating monocytic precursors (monocytes) bone marrow [17.Cox al.Origins, biology, diseases macrophages.Annu. 39: 313-344Crossref (1) monocyte contribution varies among organs. For example, steady state, microglia central nervous system (CNS) solely [18.Hoeffel G. al.C-Myb(+) progenitor-derived give rise tissue-resident macrophages.Immunity. 42: 665-678Abstract (611) while dermal embryonic origin [19.Kolter J. al.A subset skin contributes surveillance regeneration nerves.Immunity. 50: 1482-1497Abstract (69) appreciated repeatedly reviewed [20.Pathria P. al.Targeting tumor-associated cancer.Trends 40: 310-327Abstract (382) Scholar,21.Guerriero J.L. Macrophages: road less traveled, changing anticancer therapy.Trends Mol. Med. 24: 472-489Abstract (143) Similar counterparts not only its ontogeny, but cues, including type, organ, subanatomic Identifying basis over past [5.Lopez-Yrigoyen advancements unveiling multidimensional complexity manner. research, oncology eventually fully understand cells hopefully use improve precision diagnosis therapy. Single RNA sequencing (scRNA-seq) technology revolutionized providing in-depth transcriptome level [22.Giladi al.Single-cell characterization haematopoietic trajectories homeostasis perturbed haematopoiesis.Nat. Cell Biol. 20: 836-846Crossref (139) substantial advances available experimental techniques bioinformatics pipelines years, scRNA-seq investigate [23.Lawson D.A. al.Tumour resolution.Nat. 1349-1360Crossref (230) Scholar,24.Ren X. al.Insights gained analysis microenvironment.Annu. 583-609Crossref (15) transcriptomic remain Two large-scale pan-cancer provided valuable regarding diversity. One study analyzed myeloid 380 samples across 15 210 patients through combination newly collected eight published [25.Cheng transcriptional atlas infiltrating cells.Cell. 184: 792-809Abstract (111) Comparison consistent presence CD14+ CD16+ tumor-infiltrating (TIMs), LYVE1+ interstitial non-cancer tissues, seven clusters: INHBA+ C1QC+ ISG15+ LNRP3+ SPP1+ compiled mononuclear phagocytes (MNPs) isolated 41 13 types, six common universe, termed MNP-VERSE. Monocyte clusters were then extracted reintegrated generate MoMac-VERSEi. regulatory inference (SCENIC) [26.Aibar al.SCENIC: clustering.Nat. Methods. 1083-1086Crossref (1003) authors classical monocytes, nonclassical five (HES1 TAM, C1Qhi TREM2 IL4I1 proliferating TAMs) Although nomenclatures studies, others, pattern transcriptomics By reviewing journals, found preserved (Table 1). Based signature genes, enriched pathways, predicated naming interferon-primed (IFN-TAMs), (Reg-TAMs), inflammatory cytokine-enriched (Inflam-TAMs), lipid-associated (LA-TAMs), pro-angiogenic (Angio-TAMs), RTM-like (RTM-TAMs), (Prolif-TAMs) Figure 1, Key figure). Furthermore, three TIMs Box 1).Table 1Mouse various TMEsaBlack font: genes clusters; blue protein markers Underline: CITE-seq; Bold: key reported than paper., bAbbreviations: BRCA, breast cancer; CAF, cancer-associated macrophage; CITE-seq, indexing transcriptomes epitopes sequencing; CRC, colorectal CyTOF, Mass cytometry flight; ECM, matrix; ESCA, esophageal carcinoma; GC, gastric HCC, hepatocellular HNC, head neck i.v., intravenous; IF, immunofluorescent staining; INs-seq, intracellular staining LCM, laser capture microdissection; LYM, lymphoma; MEL, melanoma; Mets, metastasis; mIHC, multiplex immunochemistry MMY, myeloma; N/A, available; NPC, nasopharyngeal NSCLC, nonsmall lung OS, osteosarcoma; OVC, ovarian PDAC, pancreatic ductal adenocarcinoma; PRAC, prostate RCC, renal Reg-TAMs, TAMs; SARC, sarcoma; sc-MS, mass spectrometry; SEPN, spinal ependymomas; SKC, ST, transcriptomics; s.c., subcutaneous; macrophages; THCA, thyroid UCEC, uterine corpus endometrial carcinoma.AnnotationSpeciesSignatureTFCancer typeFunction/enriched pathwayAssayRefsIFN-TAMsHumanCASP1, CASP4, CCL2/3/4/7/8, CD274hi, CD40, CXCL2/3/9/10/11, IDO1, IFI6, IFIT1/2/3, IFITM1/3, IRF1, IRF7, ISG15, LAMP3, PDCD1LG2hi, TNFSF10, C1QA/C, CD38, IL4I1, IFI44LSTAT1 IRF1/7BRCACRCCRC metsGBMHCCHNCLYMMELMMYNPCNSCLCOSPDACSEPNTHCAUCECApoptosis regulatorsEnhance proliferationInflammatory responsesPromote Treg entry tumorT exhaustionImmunosuppressionColocalization exhausted T (ST, IF)Decreased antigen presentation (CyTOF)Suppressed activation (in vitro)IFN-α/γ-IFN response signature; IL2/STAT5; IL6/JAK/STAT3scRNA-seqCITE-seqmIHCSTNanoString GeoMx[12.Mulder Scholar,29.Gubin M.M. al.High-dimensional delineates lymphoid compartment during successful immune-checkpoint therapy.Cell. 175: 1014-1030Abstract (165) Scholar,32.Zavidij O. reveals compromised precursor stages myeloma.Nat. Cancer. 1: 493-506Crossref 33.Zhou intratumoral immunosuppressive osteosarcoma.Nat. Commun. 11: 6322Crossref (74) 34.Zhang Q. al.Interrogation microenvironmental ependymomas dual macrophages.Nat. 12: 6867Crossref (0) Scholar,45.Wu al.Spatiotemporal level.Cancer 134-153Crossref (10) Scholar,52.Pombo Antunes A.R. profiling glioblastoma species disease stage competition specialization.Nat. Neurosci. 595-610Crossref (78) Scholar,\81.Wu S.Z. spatially resolved cancers.Nat. Genet. 53: 1334-1347Crossref (47) Scholar,83.Pelka al.Spatially organized multicellular hubs cancer.Cell. 4734-4752Abstract (29) Scholar]CD14+, CD11b+, CD68+, PD-L1hi, PD-L2hi, CD80hi, CD86hi, MHCIIhi, CD86+, MRC1–, SIGLEC1–, HLA-DRlo, CD314+, CD107a+, CD86, TLR4, CD44 (CITE-seq)MouseCcl2/7/8, Cd274, Cxcl9/10/11, Ifit1/2/3, Ifit3, Ifitm1/3, Il7r, Isg15, Nos2, Rsad2, Tnfsf10, Stat1N/ACT26 s.c. CRCCT26 intrasplenic mets modelT3 SARC (s.c.)Orthotopic GL261 GBMIFN signaturescRNA-seqCITE-seqmIHC[29.Gubin Scholar]Inflam-TAMsHumanCCL2/3/4/5/20, CCL3L1, CCL3L3, CCL4L2, CCL4L4, CXCL1/2/3/5/8, G0S2, IL1B, IL1RN, IL6, INHBA, KLF2/6, NEDD9, PMAIP1, S100A8/A9, SPP1EGR3 IKZF1 NFKB1 NFE2L2 RELCRCCRC metsOSSEPNGCRecruiting regulating cellsCNS inflammation-associated chemokinesPromotes inflammationNeutrophil recruitment lumenT interaction (IHC)TNF signaling; WNTImmune check pointsscRNA-seqmIHCNanoString GeoMx[31.Che L.-H. metastases reprogramming preoperative chemotherapy.Cell Discovery. 7: 80Crossref (4) Scholar,33.Zhou Scholar,34.Zhang Scholar,42.Sathe genomic microenvironment.Clin. Cancer 26: 2640-2653Crossref (66) 43.Zhang al.Dissecting underlying premalignant lesions cancer.Cell 27: 1934-1947Abstract (104) 44.Yin H. map development using sequencing.Front. 12728169Crossref 45.Wu Scholar]MouseCxcl1/2/3/5/8, Ccl20, Ccl3l1, Il1rn, Il1b, G0s2, Inhba, Spp1N/ACT26 CRC CT26 modelChemokine productionImmunosuppressionscRNA-seq[45.Wu Scholar]LA-TAMsHumanACP5, AOPE, APOC1, ATF1, C1QA/B/C, CCL18, CD163, CD36, CD63, CHI3L1, CTSB/D/L, F13A1, FABP5, FOLR2, GPNMB, IRF3, LGALS3, LIPA, LPL, MACRO, MerTK, MMP7/9/12, MRC1, NR1H3, NRF1, NUPR1, PLA2G7, RNASE1, SPARC, SPP1, TFDP2, TREM2, ZEB1FOS/JUN HIF1A MAF/MAFB NR1H3 TCF4 TFECBRCACRCCRC metsGBMGCHCCHNCNPCNSCLCOSPDACPhagocytosisPromotion EMTComplement activationECM degradationAntigen processing pathwaysATP biosynthetic processesCanonical M2-like pathwaysFatty acid metabolismImmunosuppressionInflammationIron ion signalingscRNA-seqSMART-seq2CITE-seqmIHCST[12.Mulder Scholar,27.Zilionis R. cancers conserved populations individuals species.Immunity. 1317-1334Abstract (424) Scholar,28.Yang non-small differences sexes.Front. 12756722Google Scholar,30.Zhang analyses inform myeloid-targeted therapies colon 181: 442-459Abstract (246) Scholar,31.Che Scholar,50.Chen Y.P. subtypes associated prognosis carcinoma.Cell 30: 1024-1042Crossref (71) Scholar,81.Wu Scholar]CD9+, CD80+, MAF, CD163lo/-, CD206+/lo, CD71+, CD72+, CD73, ICOSL, CD40LG, Thy-1 (CITE-seq)MouseAcp5, Apoc1, Apoe, C1qa/B/C, Ccl18, Ccl8, Cd163, Cd206, Cd36, Cd63, Ctsb/d/l, Cxcl9, Fabp5, Folr2, Gpnmb, Lgals3, Macro, Mrc1, Trem2MAFCT26 Orthotopic GBM 7940b orthotopic iKras p53 PDAC metsPhagocytosisAntigen presentationFatty metabolismComplement activationscRNA-seqCITE-seqmIHC[45.Wu Scholar,46.Kemp S.B. al.Pancreatic marked complement-high blood tumor–associated macrophages.Life Alliance. 4e202000935Crossref Scholar]Angio-TAMsHumanADAM8, AREG, BNIP3, CCL2/4/20, CD300E, CD44, CD55, CEBPB, CLEC5A, CTSB, EREG, FCN1, FLT1, FN1, HES1, IL8, MIF, OLR1, PPARG, S100A8/9/12, SERPINB2, SLC2A1, SPIC, THBS1, TIMP1, VCAN, VEGFABACH1 CEBPB FOSL2 HIFA KLF5 MAF RUNX1 SPIC TEAD1 ZEB2BRCACRCCRCCRC metsESCAGBMGCHCCMELNPCNPCNSCLCOVCPDACPDAC metsRCCSEPNTHCAUCECAngiogenesisCAF interactionECM proteolysis; ECM interactionPromotion EMTHIF pathway; NF-kB Notch VEGF signalingJuxtaposed PLVAP+/DLL4+ endothelial (IF)scRNA-seqSMART-seq2CITE-seqNanoString GeoMx[25.Cheng Scholar,41.Sharma al.Onco-fetal drives carcinoma.Cell. 183: 377-394Abstract (103) Scholar,49.Raghavan al.Microenvironment drug 6119-6137Abstract Scholar,67.Zhao revealed promoted progression.J. Transl. 454Crossref Scholar]CD52hi, CD163hi, CD206hi, CXCR4+, CD354+, FOSL2, VEGFAMouseArg1, Adam8, Bnip3, Mif, Slc2a1N/AOrthotopic modelHIF signalingAngiogenesisscRNA-seqCITE-seq[52.Pombo Scholar]Reg-TAMsHumanCCL2, CD274, CD80, CHIT1, CX3CR1, HLA-A/C, HLA-DQA1/B1, HLA-DRA/B1/B5, ICOSLG, IL-10, ITGA4, LGALS9, MAC

Language: Английский

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Breast cancer as an example of tumour heterogeneity and tumour cell plasticity during malignant progression

British Journal of Cancer, Journal Year: 2021, Volume and Issue: 125(2), P. 164 - 175

Published: April 6, 2021

Heterogeneity within a tumour increases its ability to adapt constantly changing constraints, but adversely affects patient's prognosis, therapy response and clinical outcome. Intratumoural heterogeneity results from combination of extrinsic factors the microenvironment intrinsic parameters cancer cells themselves, including their genetic, epigenetic transcriptomic traits, proliferate, migrate invade, stemness plasticity attributes. Cell constitutes rapidly reprogramme gene expression repertoire, change behaviour identities, microenvironmental cues. These features also directly contribute are critical for malignant progression. In this article, we use breast as an example origins (in particular, mutational spectrum clonal evolution progressing tumours) cell that shown by undergoing epithelial-to-mesenchymal transition), well considering interclonal cooperativity sources heterogeneity. We review current knowledge on functional contribution progression, metastasis formation resistance.

Language: Английский

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Emergence of a High-Plasticity Cell State during Lung Cancer Evolution

Cancer Cell, Journal Year: 2020, Volume and Issue: 38(2), P. 229 - 246.e13

Published: July 23, 2020

Language: Английский

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The single-cell sequencing: new developments and medical applications

Cell & Bioscience, Journal Year: 2019, Volume and Issue: 9(1)

Published: June 26, 2019

Single-cell sequencing technologies can be used to detect the genome, transcriptome and other multi-omics of single cells. They show differences evolutionary relationships various This review introduces latest advances in single-cell their applications oncology, microbiology, neurology, reproduction, immunology, digestive urinary systems, highlighting important role that techniques play these areas.

Language: Английский

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Transcriptional diversity and bioenergetic shift in human breast cancer metastasis revealed by single-cell RNA sequencing

Nature Cell Biology, Journal Year: 2020, Volume and Issue: 22(3), P. 310 - 320

Published: March 1, 2020

Language: Английский

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