Author

Hervé Avet‐Loiseau

Centre de Recherches en Cancérologie de ToulouseORCID 0000-0002-3050-0140Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Cancer Biology· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Approach:statistical model· 3 Assay:whole-genome sequencing· 3 Approach:benchmark study· 1 Research Focus:cancer & tumor microenvironment· 1 Research Focus:differential expression· 1 Research Focus:variant calling· 1

Frequent Co-Authors

Jill CorreiD· 2 shared Nikhil C. MunshiiD· 2 shared Ahmet DoǧaniD· 1 shared Alessandro LaganàiD· 1 shared Alice CleyneniD· 1 shared Angela Hamblin· 1 shared Anjan ThakurtaiD· 1 shared Benjamin T. DiamondiD· 1 shared

Activity by Year

2019-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersCancer Biology

Jill CorreORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Sequential acquisition of 1p31.1-p12 LOH and 1q Gain is a common double-hit event in relapsed/refractory myeloma

Naser Ansari‐Pour, Sarah Gooding, Mohammad H. Kazeroun, Seyed Alireza Hasheminasab, Evie Fitzsimons, Selina J Chavda, Alessandro Laganà, Erin Flynt, Udo C. T. Oppermann, Karthik Ramasamy, Kwee Yong, Angela Hamblin, Jill Corre, Hervé Avet‐Loiseau, Nikhil C. Munshi, , Anjan Thakurta

The paper identifies a therapy-driven genomic double-hit (1pCEN LOH and 1q gain) in relapsed/refractory myeloma, associated with poor prognosis and clonal expansion.

bioRxiv · May 21, 2026 · PreprintCancer Biology

Unsupervized identification of prognostic copy-numberalterations using segmentation and lasso regularization

Alice Cleynen, Hervé Avet‐Loiseau, Jill Corre

The paper develops a method to identify prognostic copy-number alterations by integrating segmentation and lasso regularization, showing improved recovery of significant regions and survival prediction in multiple myeloma.

bioRxiv · Dec 14, 2022 · PreprintBioinformatics

Revealing the impact of recurrent and rare structural variants in multiple myeloma

Even Holth Rustad, Venkata D. Yellapantula, Dominik Głodzik, Kylee H. Maclachlan, Benjamin T. Diamond, Eileen Mary Boyle, Cody Ashby, Patrick Blaney, Gunes Gundem, Malin L. Hultcrantz, Daniel A. Leongamornlert, Nicos Angelopoulos, Daniel Auclair, Yanming Zhang, Ahmet Doǧan, , Francesco Maura

This study identifies 100 SV hotspots and 31 new candidate driver genes in multiple myeloma, revealing that 63% of SVs remain unexplained and are associated with outlier gene expression.

bioRxiv · Dec 18, 2019 · PreprintGenomics