Computational Biomedicine

Selected Publications

Multimodal analysis unveils tumor microenvironment heterogeneity linked to immune activity and evasion

Lapuente-Santana O., Sturm G. et al. iScience 27(8), 110529 (2024).

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Interpretable systems biomarkers predict response to immune-checkpoint inhibitors

Lapuente-Santana O. et al. Patterns 2(8), 100293 (2021).

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Next-generation computational tools for interrogating cancer immunity.

Finotello F. et al. Nature Reviews Genetics 20(12), 724–746 (2019).

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Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data

Finotello F. et al. Genome Medicine 11(1), 34 (2019).

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Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade

Charoentong P.*, Finotello F*, Angelova M.* et al. Cell Reports 18(1), 248-262 (2017).

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All Publications

• Multimodal analysis unveils tumor microenvironment heterogeneity linked to immune activity and evasion
  Lapuente-Santana Ó, Sturm G, Kant J, Ausserhofer M, Zackl C, Zopoglou M, McGranahan N, Rieder D, Trajanoski Z, da Cunha Carvalho de Miranda NF, Eduati F, Finotello F.
  iScience, 27(8):110529 (2024).


• A spatial architecture-embedding HLA signature to predict clinical response to immunotherapy in renal cell carcinoma
  Kinget L, Naulaerts S, Govaerts J, Vanmeerbeek I, Sprooten J, Laureano RS, Dubroja N, Shankar G, Bosisio FM, Roussel E, Verbiest A, Finotello F, Ausserhofer M, Lambrechts D, Boeckx B, Wozniak A, Boon L, Kerkhofs J, Zucman-Rossi J, Albersen M, Baldewijns M, Beuselinck B, Garg AD.
  Nat Med, 30(6):1667-1679 (2024).


• Tumor-targeted therapy with BRAF-inhibitor recruits activated dendritic cells to promote tumor immunity in melanoma
  Hornsteiner F, Vierthaler J, Strandt H, Resag A, Fu Z, Ausserhofer M, Tripp CH, Dieckmann S, Kanduth M, Farrand K, Bregar S, Nemati N, Hermann-Kleiter N, Seretis A, Morla S, Mullins D, Finotello F, Trajanoski Z, Wollmann G, Ronchese F, Schmitz M, Hermans IF, Stoitzner P.
  J Immunother Cancer, 12(4):e008606 (2024).


• Single-cell Profiling of Reprogrammed Human Neural Stem Cells Unveils High Similarity to Neural Progenitors in the Developing Central Nervous System
  Spathopoulou A, Podlesnic M, De Gaetano L, Kirsch EM, Tisch M, Finotello F, Aigner L, Günther K, Edenhofer F.
  Stem Cell Rev Rep, 20(5):1325-1339 (2024).


• Making mouse transcriptomics deconvolution accessible with immunedeconv
  Merotto L, Sturm G, Dietrich A, List M, Finotello F.
  Bioinform Adv, 4(1):vbae032 (2024).


• The highly selective and oral phosphoinositide 3-kinase delta (PI3K-δ) inhibitor roginolisib induces apoptosis in mesothelioma cells and increases immune effector cell composition
  Kalla C, Ott G, Finotello F, Niewola-Staszkowska K, Conza GD, Lahn M, van der Veen L, Schüler J, Falkenstern-Ge R, Kopecka J, Riganti C.
  Transl Oncol, 43:101857 (2024).


• A community challenge to predict clinical outcomes after immune checkpoint blockade in non-small cell lung cancer
  Mason M, Lapuente-Santana Ó, Halkola AS, Wang W, Mall R, Xiao X, Kaufman J, Fu J, Pfeil J, Banerjee J, Chung V, Chang H, Chasalow SD, Lin HY, Chai R, Yu T, Finotello F, Mirtti T, Mäyränpää MI, Bao J, Verschuren EW, Ahmed EI, Ceccarelli M, Miller LD, Monaco G, Hendrickx WRL, Sherif S, Yang L, Tang M, Gu SS, Zhang W, Zhang Y, Zeng Z, Das Sahu A, Liu Y, Yang W, Bedognetti D, Tang J, Eduati F, Laajala TD, Geese WJ, Guinney J, Szustakowski JD, Vincent BG, Carbone DP.
  J Transl Med, 22(1):190 (2024).


• Next-generation deconvolution of transcriptomic data to investigate the tumor microenvironment
  Merotto L, Zopoglou M, Zackl C, Finotello F.
  Int Rev Cell Mol Biol, 382:103-143 (2024).


• Functional and spatial proteomics profiling reveals intra- and intercellular signaling crosstalk in colorectal cancer
  Plattner C, Lamberti G, Blattmann P, Kirchmair A, Rieder D, Loncova Z, Sturm G, Scheidl S, Ijsselsteijn M, Fotakis G, Noureen A, Lisandrelli R, Böck N, Nemati N, Krogsdam A, Daum S, Finotello F, Somarakis A, Schäfer A, Wilflingseder D, Gonzalez Acera M, Öfner D, Huber LA, Clevers H, Becker C, Farin HF, Greten FR, Aebersold R, de Miranda NFCC, Trajanoski Z.
  iScience, 26(12):108399 (2023).


• Single cell dynamics of tumor specificity vs bystander activity in CD8(+) T cells define the diverse immune landscapes in colorectal cancer
  Borràs DM, Verbandt S, Ausserhofer M, Sturm G, Lim J, Verge GA, Vanmeerbeek I, Laureano RS, Govaerts J, Sprooten J, Hong Y, Wall R, De Hertogh G, Sagaert X, Bislenghi G, D'Hoore A, Wolthuis A, Finotello F, Park WY, Naulaerts S, Tejpar S, Garg AD.
  Cell Discov, 9(1):114 (2023).


• The scverse project provides a computational ecosystem for single-cell omics data analysis
  Virshup I, Bredikhin D, Heumos L, Palla G, Sturm G, Gayoso A, Kats I, Koutrouli M; Scverse Community; Berger B, Pe'er D, Regev A, Teichmann SA, Finotello F, Wolf FA, Yosef N, Stegle O, Theis FJ.
  Nat Biotechnol, 41(5):604-606 (2023).


• Role of the Extracytoplasmic Function Sigma Factor SigE in the Stringent Response of Mycobacterium tuberculosis
  Baruzzo G, Serafini A, Finotello F, Sanavia T, Cioetto-Mazzabò L, Boldrin F, Lavezzo E, Barzon L, Toppo S, Provvedi R, Manganelli R, Di Camillo B.
  Microbiol Spectr, 11(2):e0294422 (2023).


• MAST: a hybrid Multi-Agent Spatio-Temporal model of tumor microenvironment informed using a data-driven approach
  Cesaro G, Milia M, Baruzzo G, Finco G, Morandini F, Lazzarini A, Alotto P, da Cunha Carvalho de Miranda NF, Trajanoski Z, Finotello F, Di Camillo B.
  Bioinform Adv, 2(1):vbac092 (2022).


• High-resolution single-cell atlas reveals diversity and plasticity of tissue-resident neutrophils in non-small cell lung cancer
  Salcher S, Sturm G, Horvath L, Untergasser G, Kuempers C, Fotakis G, Panizzolo E, Martowicz A, Trebo M, Pall G, Gamerith G, Sykora M, Augustin F, Schmitz K, Finotello F, Rieder D, Perner S, Sopper S, Wolf D, Pircher A, Trajanoski Z.
  Cancer Cell, 40(12):1503-1520.e8 (2022).


• What are the current driving questions in immune repertoire research?
  Greiff V, Luning Prak ET, O'Donnell T, Finotello F, Reddy ST, Walczak A, Mora T.
  Cell Syst, 13(9):683-686 (2022).


• SimBu: bias-aware simulation of bulk RNA-seq data with variable cell-type composition
  Dietrich A, Sturm G, Merotto L, Marini F, Finotello F, List M.
  Bioinformatics, 38(Suppl_2):ii141-ii147 (2022).


• Tumor-specific T cells support chemokine-driven spatial organization of intratumoral immune microaggregates needed for long survival
  Abdulrahman Z, Santegoets SJ, Sturm G, Charoentong P, Ijsselsteijn ME, Somarakis A, Höllt T, Finotello F, Trajanoski Z, van Egmond SL, Mustafa DAM, Welters MJP, de Miranda NFCC, van der Burg SH.
  J Immunother Cancer, 10(2):e004346 (2022).


• CD161 expression and regulation defines rapidly responding effector CD4+ T cells associated with improved survival in HPV16-associated tumors
  Duurland CL, Santegoets SJ, Abdulrahman Z, Loof NM, Sturm G, Wesselink TH, Arens R, Boekestijn S, Ehsan I, van Poelgeest MIE, Finotello F, Hackl H, Trajanoski Z, Ten Dijke P, Braud VM, Welters MJP, van der Burg SH.
  J Immunother Cancer, 10(1):e003995 (2022).


• nextNEOpi: a comprehensive pipeline for computational neoantigen prediction
  Rieder D, Fotakis G, Ausserhofer M, René G, Paster W, Trajanoski Z, Finotello F.
  Bioinformatics, 38(4):1131-1132 (2022).


• NKG2A is a late immune checkpoint on CD8 T cells and marks repeated stimulation and cell division
  Borst L, Sluijter M, Sturm G, Charoentong P, Santegoets SJ, van Gulijk M, van Elsas MJ, Groeneveldt C, van Montfoort N, Finotello F, Trajanoski Z, Kiełbasa SM, van der Burg SH, van Hall T.
  Int J Cancer, 150(4):688-704 (2022).


• Stress-induced inflammation evoked by immunogenic cell death is blunted by the IRE1α kinase inhibitor KIRA6 through HSP60 targeting
  Rufo N, Korovesis D, Van Eygen S, Derua R, Garg AD, Finotello F, Vara-Perez M, Rožanc J, Dewaele M, de Witte PA, Alexopoulos LG, Janssens S, Sinkkonen L, Sauter T, Verhelst SHL, Agostinis P.
  Cell Death Differ, 29(1):230-245 (2022).


• Interpretable systems biomarkers predict response to immune-checkpoint inhibitors
  Lapuente-Santana Ó, van Genderen M, Hilbers PAJ, Finotello F, Eduati F.
  Patterns (N Y)Patterns, 2(8):100293 (2021).


• A vision of immuno-oncology: the Siena think tank of the Italian network for tumor biotherapy (NIBIT) foundation
  Maio M, Lahn M, Di Giacomo AM, Covre A, Calabrò L, Ibrahim R, Fox B; Siena Think Tank.
  J Exp Clin Cancer Res, 40(1):240 (2021).


• Editorial: Multi-omic Data Integration in Oncology
  Finotello F, Calura E, Risso D, Hautaniemi S, Romualdi C.
  Front Oncol, 10:1768 (2020).


• CD39 Identifies the CD4(+) Tumor-Specific T-cell Population in Human Cancer
  Kortekaas KE, Santegoets SJ, Sturm G, Ehsan I, van Egmond SL, Finotello F, Trajanoski Z, Welters MJP, van Poelgeest MIE, van der Burg SH.
  Cancer Immunol Res, 8(10):1311-1321 (2020).


• Mitochondrial DNA drives abscopal responses to radiation that are inhibited by autophagy
  Yamazaki T, Kirchmair A, Sato A, Buqué A, Rybstein M, Petroni G, Bloy N, Finotello F, Stafford L, Navarro Manzano E, Ayala de la Peña F, García-Martínez E, Formenti SC, Trajanoski Z, Galluzzi L.
  Nat Immunol, 21(10):1160-1171 (2020).


• Scirpy: a Scanpy extension for analyzing single-cell T-cell receptor-sequencing data
  Sturm G, Szabo T, Fotakis G, Haider M, Rieder D, Trajanoski Z, Finotello F.
  Bioinformatics, 36(18):4817-4818 (2020).


• Deconvoluting tumor-infiltrating immune cells from RNA-seq data using quanTIseq
  Plattner C, Finotello F, Rieder D.
  Methods Enzymol, 636:261-285 (2020).


• Immunedeconv: An R Package for Unified Access to Computational Methods for Estimating Immune Cell Fractions from Bulk RNA-Sequencing Data
  Sturm G, Finotello F, List M.
  Methods Mol Biol, 2120:223-232 (2020).


• In Silico Cell-Type Deconvolution Methods in Cancer Immunotherapy
  Sturm G, Finotello F, List M.
  Methods Mol Biol, 2120:213-222 (2020).


• In Silico Prediction of Tumor Neoantigens with TIminer
  Kirchmair A, Finotello F.
  Methods Mol Biol, 2120:129-145 (2020).


• NeoFuse: predicting fusion neoantigens from RNA sequencing data
  Fotakis G, Rieder D, Haider M, Trajanoski Z, Finotello F.
  Bioinformatics, 36(7):2260-2261 (2020).


• Guadecitabine Plus Ipilimumab in Unresectable Melanoma: The NIBIT-M4 Clinical Trial
  Di Giacomo AM, Covre A, Finotello F, Rieder D, Danielli R, Sigalotti L, Giannarelli D, Petitprez F, Lacroix L, Valente M, Cutaia O, Fazio C, Amato G, Lazzeri A, Monterisi S, Miracco C, Coral S, Anichini A, Bock C, Nemc A, Oganesian A, Lowder J, Azab M, Fridman WH, Sautès-Fridman C, Trajanoski Z, Maio M.
  Clin Cancer Res, 25(24):7351-7362 (2019).


• Next-generation computational tools for interrogating cancer immunity
  Finotello F, Rieder D, Hackl H, Trajanoski Z.
  Nat Rev Genet, 20(12):724-746 (2019).


• Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology
  Sturm G, Finotello F, Petitprez F, Zhang JD, Baumbach J, Fridman WH, List M, Aneichyk T.
  Bioinformatics, 35(14):i436-i445 (2019).


• Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data
  Finotello F, Mayer C, Plattner C, Laschober G, Rieder D, Hackl H, Krogsdam A, Loncova Z, Posch W, Wilflingseder D, Sopper S, Ijsselsteijn M, Brouwer TP, Johnson D, Xu Y, Wang Y, Sanders ME, Estrada MV, Ericsson-Gonzalez P, Charoentong P, Balko J, de Miranda NFDCC, Trajanoski Z.
  Genome Med, 11(1):34 (2019).


• Multi-Omics Profiling of the Tumor Microenvironment: Paving the Way to Precision Immuno-Oncology
  Finotello F, Eduati F.
  Front Oncol, 8:430 (2018).


• Optimizing PCR primers targeting the bacterial 16S ribosomal RNA gene
  Sambo F, Finotello F, Lavezzo E, Baruzzo G, Masi G, Peta E, Falda M, Toppo S, Barzon L, Di Camillo B.
  BMC Bioinformatics, 19(1):343 (2018).


• A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes
  van Zuydam NR, Ahlqvist E, Sandholm N, Deshmukh H, Rayner NW, Abdalla M, Ladenvall C, Ziemek D, Fauman E, Robertson NR, McKeigue PM, Valo E, Forsblom C, Harjutsalo V; Finnish Diabetic Nephropathy Study (FinnDiane); Perna A, Rurali E, Marcovecchio ML, Igo RP Jr, Salem RM, Perico N, Lajer M, Käräjämäki A, Imamura M, Kubo M, Takahashi A, Sim X, Liu J, van Dam RM, Jiang G, Tam CHT, Luk AOY, Lee HM, Lim CKP, Szeto CC, So WY, Chan JCN; Hong Kong Diabetes Registry Theme-based Research Scheme Project Group; Ang SF, Dorajoo R, Wang L, Clara TSH, McKnight AJ, Duffy S; Warren 3 and Genetics of Kidneys in Diabetes (GoKinD) Study Group; Pezzolesi MG; GENIE (GEnetics of Nephropathy an International Effort) Consortium; Marre M, Gyorgy B, Hadjadj S, Hiraki LT; Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) Research Group; Ahluwalia TS, Almgren P, Schulz CA, Orho-Melander M, Linneberg A, Christensen C, Witte DR, Grarup N, Brandslund I, Melander O, Paterson AD, Tregouet D, Maxwell AP, Lim SC, Ma RCW, Tai ES, Maeda S, Lyssenko V, Tuomi T, Krolewski AS, Rich SS, Hirschhorn JN, Florez JC, Dunger D, Pedersen O, Hansen T, Rossing P, Remuzzi G; SUrrogate markers for Micro- and Macrovascular hard endpoints for Innovative diabetes Tools (SUMMIT) Consortium; Brosnan MJ, Palmer CNA, Groop PH, Colhoun HM, Groop LC, McCarthy MI.
  Diabetes, 67(7):1414-1427 (2018).


• Deviations of the immune cell landscape between healthy liver and hepatocellular carcinoma
  Rohr-Udilova N, Klinglmüller F, Schulte-Hermann R, Stift J, Herac M, Salzmann M, Finotello F, Timelthaler G, Oberhuber G, Pinter M, Reiberger T, Jensen-Jarolim E, Eferl R, Trauner M.
  Sci Rep, 8(1):6220 (2018).


• Quantifying tumor-infiltrating immune cells from transcriptomics data
  Finotello F, Trajanoski Z.
  Cancer Immunol Immunother, 67(7):1031-1040 (2018).


• Targeting immune checkpoints potentiates immunoediting and changes the dynamics of tumor evolution
  Efremova M, Rieder D, Klepsch V, Charoentong P, Finotello F, Hackl H, Hermann-Kleiter N, Löwer M, Baier G, Krogsdam A, Trajanoski Z.
  Nat Commun, 9(1):32 (2018).


• Neoantigens Generated by Individual Mutations and Their Role in Cancer Immunity and Immunotherapy
  Efremova M, Finotello F, Rieder D, Trajanoski Z.
  Front Immunol, 8:1679 (2017).


• TIminer: NGS data mining pipeline for cancer immunology and immunotherapy
  Tappeiner E, Finotello F, Charoentong P, Mayer C, Rieder D, Trajanoski Z.
  Bioinformatics, 33(19):3140-3141 (2017).


• Analysis of High-Throughput RNA Bisulfite Sequencing Data
  Rieder D, Finotello F.
  Methods Mol Biol, 1562:143-154 (2017).


• New strategies for cancer immunotherapy: targeting regulatory T cells
  Finotello F, Trajanoski Z.
  Genome Med, 9(1):10 (2017).


• Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade
  Charoentong P, Finotello F, Angelova M, Mayer C, Efremova M, Rieder D, Hackl H, Trajanoski Z.
  Cell Rep, 18(1):248-262 (2017).


• Measuring the diversity of the human microbiota with targeted next-generation sequencing
  Finotello F, Mastrorilli E, Di Camillo B.
  Brief Bioinform, 19(4):679-692 (2018).


• Computational genomics tools for dissecting tumour-immune cell interactions
  Hackl H, Charoentong P, Finotello F, Trajanoski Z.
  Nat Rev Genet, 17(8):441-58 (2016).


• Inferring causal molecular networks: empirical assessment through a community-based effort
  Hill SM, Heiser LM, Cokelaer T, Unger M, Nesser NK, Carlin DE, Zhang Y, Sokolov A, Paull EO, Wong CK, Graim K, Bivol A, Wang H, Zhu F, Afsari B, Danilova LV, Favorov AV, Lee WS, Taylor D, Hu CW, Long BL, Noren DP, Bisberg AJ; HPN-DREAM Consortium; Mills GB, Gray JW, Kellen M, Norman T, Friend S, Qutub AA, Fertig EJ, Guan Y, Song M, Stuart JM, Spellman PT, Koeppl H, Stolovitzky G, Saez-Rodriguez J, Mukherjee S.
  Nat Methods, 13(4):310-8 (2016).


• EEG signal features extraction based on fractal dimension
  Finotello F, Scarpa F, Zanon M.
  Annu Int Conf IEEE Eng Med Biol Soc, 2015:4154-7 (2015).


• FunPat: function-based pattern analysis on RNA-seq time series data
  Sanavia T, Finotello F, Di Camillo B.
  BMC Genomics, 16(Suppl 6):S2 (2015).


• Measuring differential gene expression with RNA-seq: challenges and strategies for data analysis
  Finotello F, Di Camillo B.
  Brief Funct Genomics, 14(2):130-42 (2015).


• Global genomic and transcriptomic analysis of human pancreatic islets reveals novel genes influencing glucose metabolism
  Fadista J, Vikman P, Laakso EO, Mollet IG, Esguerra JL, Taneera J, Storm P, Osmark P, Ladenvall C, Prasad RB, Hansson KB, Finotello F, Uvebrant K, Ofori JK, Di Camillo B, Krus U, Cilio CM, Hansson O, Eliasson L, Rosengren AH, Renström E, Wollheim CB, Groop L.
  Proc Natl Acad Sci U S A, 111(38):13924-9 (2014).


• Reducing bias in RNA sequencing data: a novel approach to compute counts
  Finotello F, Lavezzo E, Bianco L, Barzon L, Mazzon P, Fontana P, Toppo S, Di Camillo B.
  BMC Bioinformatics, 15 Suppl 1(Suppl 1):S7 (2014).


• Genomic comparative analysis and gene function prediction in infectious diseases: application to the investigation of a meningitis outbreak
  Lavezzo E, Toppo S, Franchin E, Di Camillo B, Finotello F, Falda M, Manganelli R, Palù G, Barzon L.
  BMC Infect Dis, 13:554 (2013).


• Comparative analysis of algorithms for whole-genome assembly of pyrosequencing data
  Finotello F, Lavezzo E, Fontana P, Peruzzo D, Albiero A, Barzon L, Falda M, Di Camillo B, Toppo S.
  Brief Bioinform, 13(3):269-80 (2012).


• Draft genome sequences of two Neisseria meningitidis serogroup C clinical isolates
  Lavezzo E, Toppo S, Barzon L, Cobelli C, Di Camillo B, Finotello F, Franchin E, Peruzzo D, Toffolo GM, Trevisan M, Palù G.
  J Bacteriol, 192(19):5270-1 (2010).