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Gollob, K. J.

Publications and source records attributed to Gollob, K. J..

2 recordsLinked to original sources

Wiring multiple microenvironment proteomes uncovers the biology in head and neck cancer

The poor prognosis of head and neck cancer (HNC) is associated with the presence of metastasis within the lymph nodes (LNs). Herein, the proteome of 140 multisite samples from a 59-HNC patient cohort, including primary and matched LN-negative or -positive tissues, saliva, and blood cells, reveals insights into the biology and potential metastasis biomarkers that may assist in clinical decision making. Protein profiles are strictly associated with immune modulation across datasets, and this provides the basis for investigating immune markers associated with metastasis. The proteome of LN metastatic cells recapitulates the proteome of the primary tumor sites. Conversely, the LN microenvironment proteome highlights the candidate prognostic markers. By integrating prioritized peptide, protein, and transcript levels with machine learning models, we identified a nodal metastasis signature in the blood and saliva. In summary, we present the deepest proteome characterization wiring multiple sampling sites in HNC, thus providing a promising basis for understanding tumoral biology and identifying metastasis-associated signatures.

cancer biology↗

A genome-wide association study highlights a regulatory role for IFNG-AS1 contributing to cutaneous leishmaniasis in Brazil

BackgroundCutaneous leishmaniasis (CL) caused by Leishmania braziliensis remains an important public health problem in Brazil. The goal of this study was to identify genetic risk factors for CL. MethodsGenome-wide analysis was undertaken using DNAs from 956 CL cases and 868 controls (phase 1) and 1110 CL cases and 1178 controls (phase 2) genotyped using Illumina HumanCoreExome BeadChips. Imputation against 1000G data provided 4,498,586 quality-controlled single nucleotide variants (SNVs) common across phase 1 and phase 2 samples. Linear mixed models in FastLMM were used to take account of genetic diversity/ethnicity/admixture. Cellular cytokines were measured using flow cytometry. ResultsCombined analysis across cohorts found no associations that achieved genome-wide significance, commonly accepted as P<5x10-8. Support for variants at wound-healing genes previously studied as candidate genes for CL included SMAD2 (rs115582038/rs75753347; Pimputed_1000G=1.47x10-4). Top novel GWAS hits at P<5x10-5 in plausible candidate genes for CL included SERPINB10 (rs62097497;Pimputed_1000G=2.67x10-6), CRLF3 (rs75270613; Pimputed_1000G=5.12x10-6), STX7 (rs144488134;Pimputed_1000G=6.06x10-6), KRT80 (rs10783496 Pimputed_1000G=6.58x10-6), LAMP3 (rs74285558;Pimputed_1000G=6.54x10-6) and IFNG-AS1 (rs4913269;Pimputed_1000G=1.32x10-5). Of these, LAMP3 (Padjusted=9.25x10-12; +6-fold), STX7 (Padjusted=7.62x10-3; +1.3-fold) and CRLF3 (Padjusted=9.19x10-9; +1.97-fold) were all expressed more highly in CL biopsies compared to normal skin, whereas expression of KRT80 (Padjusted=3.07x10-8; -3-fold) was lower. Notably, the percent peripheral blood CD3+ T cells making interferon-{gamma} in response to Leishmania antigen differed significantly by IFNG-AS1 genotype. ConclusionsIn addition to supporting variants in wound-healing genes as genetic risk factors for CL, our GWAS results provide important novel leads to understanding pathogenesis of CL including through the regulation of interferon-{gamma} responses.

genetics↗