Author

T. M. Malta

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

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Cancer Biology· 7

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 6 Research Focus:differential expression· 5 Organism:human· 5 Assay:bulk RNA-seq· 4 Assay:DNA methylation· 4 Approach:statistical model· 4 Research Focus:gene regulatory network inference· 3 Approach:experimental assay· 2

Frequent Co-Authors

H. Noushmehr· 6 shared T. S. Sabedot· 4 shared J. Snyder· 3 shared L. M. Poisson· 3 shared A. V. Castro· 2 shared J. Rock· 2 shared L. F. Stead· 2 shared M. Wells· 2 shared

Activity by Year

2017-2023 · peak 2/yr

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10 top collaborators · 39 mutual co-author links

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6 shared papersCancer Biology

H. Noushmehr

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7 papers

Recent·Most cited

Machine learning determines stemness associated with simple and basal-like canine mammary carcinomas

P. L. P. Xavier, M. Marcao, R. L. Simoes, M. E. G. Job, R. d. F. Strefezzi, H. Fukumasu, T. M. Malta

The paper uses machine learning to assess stemness in canine mammary tumors, finding higher stemness in simple carcinomas and linking it to basal-like tumors and specific gene signatures.

bioRxiv · Oct 9, 2023Cancer Biology

Longitudinal analysis of diffuse glioma reveals cell state dynamics at recurrence associated with changes in genetics and the microenvironment

F. S. Varn, K. C. Johnson, T. E. Wade, T. M. Malta, T. S. Sabedot, F. P. Barthel, H. Kim, N. Ahmed, I. Datta, J. S. Barnholtz-Sloan, S. Bakas, F. D'Angelo, H. K. Gan, L. Garofano, J. T. Huse, , The GLASS Consortium

This study analyzes longitudinal glioma data to identify recurrence-associated changes in genetics and microenvironment linked to therapy resistance.

bioRxiv · May 3, 2021Cancer Biology

DNA Methylation-based Signatures Classify Sporadic Pituitary Tumors According to Clinicopathological Features.

M. S. Mosella, T. S. Sabedot, T. C. Silva, T. M. Malta, F. D. Segato, K. P. Asmaro, M. Wells, A. Mukherjee, L. M. Poisson, J. Snyder, A. C. deCarvalho, T. Walbert, T. Aho, S. Kalkanis, P. C. Elias, , A. V. Castro

This paper identifies and validates DNA methylation signatures that classify sporadic pituitary tumors based on clinicopathological features and adenohypophyseal cell lineages.

Neuro-Oncology · Feb 25, 2021Peer-reviewedCancer Biology

Primary and recurrent glioma patient-derived orthotopic xenografts (PDOX) represent relevant patient avatars for precision medicine

A. Golebiewska, A.-C. Hau, A. Oudin, D. Stieber, Y. A. Yabo, V. Baus, V. Barthelemy, E. Klein, S. Bougnaud, O. Keunen, M. Wantz, A. Michelucci, V. Neirinckx, A. Muller, T. Kaoma, , S. P. Niclou

This study shows that glioma PDOX models accurately represent patient tumors and can predict treatment responses in personalized medicine.

bioRxiv · Apr 24, 2020Cancer Biology

Predicting master transcription factors from pan-cancer expression data

J. Reddy, M. A. S. Fonseca, R. I. Corona, R. Nameki, F. Segato Dezem, I. A. Klein, H. Chang, D. Chaves-Moreira, L. Afeyan, T. M. Malta, X. Lin, F. Abbasi, A. Font-Tello, T. Sabedot, P. Cejas, , K. Lawrenson

This paper introduces CaCTS, an algorithm that identifies candidate master transcription factors (MTFs) across 34 cancer types using RNA-seq data, revealing novel MTFs and functional groupings.

bioRxiv · Nov 12, 2019Cancer Biology

Detection of glioma and prognostic subtypes by non-invasive circulating cell-free DNA methylation markers

H. Noushmehr, T. S. Sabedot, T. M. Malta, K. Nelson, J. Snyder, M. Wells, A. deCarvalho, A. Makherjee, D. Chitale, M. Mosella, K. Asmaro, A. M. Robin, M. L. Rosenblum, T. Mikkelsen, J. Rock, , A. V. Castro

This study identifies non-invasive circulating DNA methylation markers that can detect glioma and predict its prognosis from serum samples.

bioRxiv · Apr 8, 2019 · PreprintCancer Biology

Glioma CpG Island Methylator Phenotype (G-CIMP): Biological and Clinical Implications

T. M. Malta, C. F. Souza, T. S. Sabedot, T. C. Silva, M. Q. S. Mosella, S. N. Kalkanis, J. Snyder, A. V. B. Castro, H. Noushmehr

This paper reviews the biological and clinical implications of G-CIMP subsets in gliomas, highlighting their role in prognosis and potential for personalized therapy.

bioRxiv · Sep 14, 2017Cancer Biology