Biology subjects

Baron, J. A.

Publications and source records attributed to Baron, J. A..

3 recordsLinked to original sources

bioRxiv2026

Differences in T-cell counts and neighborhood patterns in human colorectal adenomas and sessile serrated lesions

BackgroundT-cell responses influence recurrence and survival in colorectal cancer. T-cell subset distributions vary by molecular phenotype and location, shaping cytotoxic or immune-cold tumor immune microenvironments (TiMEs). However, the T-cell contexture and their spatial proximities within preinvasive lesions are not well characterized. MethodsWe analyzed sessile serrated lesions (SSLs), tubulovillous/villous adenomas (TVs), and tubular adenomas (TAs) from three completed studies (N=120). Whole-slide multiplex immunofluorescence was used to quantify eight T-cell subsets (CD4, CD8, Th1, Th17, Treg, Tc1, Tc17, TcTreg). Counts were compared by histology using a generalized linear mixed model with a negative binomial distribution, including an offset for total cell counts and adjusting for age, sex, anatomic location, and lesion size. Nearest-neighbor (NN) analyses assessed proximities of T-cell pairs across lesion types. ResultsTAs and SSLs had higher CD4 and CD8 T-cell counts compared with TVs (q<0.05). SSLs had lower Th17 counts than TAs (q<0.05) and compared with TVs leaned toward fewer Tregs (q=0.07). NN analysis showed that TVs, compared with SSLs and TAs, had increased Treg clustering. In contrast, TA versus SSL comparisons revealed predominant CD4 clustering with Th17, Th1, and CD8 subsets. ConclusionTVs are characterized by lower T-cell infiltration and a greater tendency for regulatory T-cell clustering, consistent with an immune-cold TiME relative to TAs. SSLs and TAs were both more immune-infiltrated than TVs, but SSLs appeared less inflamed and less dominated by regulatory subsets. In contrast, CD4dominant clustering in TAs suggested stronger helper coordination. Preinvasive lesions therefore demonstrate immune and spatial heterogeneity by lesion types.

pathology↗

bioRxiv2020

A combined proteomics and Mendelian randomization approach to investigate the effects of aspirin-targeted proteins on colorectal cancer

BackgroundEvidence for aspirins chemopreventative properties on colorectal cancer (CRC) is substantial, but its mechanism of action is not well-understood. We combined a proteomic approach with Mendelian randomization (MR) to identify possible new aspirin targets that decrease CRC risk. MethodsHuman colorectal adenoma cells (RG/C2) were treated with aspirin (24 hours) and a stable isotope labelling with amino acids in cell culture (SILAC) based proteomics approach identified altered protein expression. Protein quantitative trait loci (pQTLs) from INTERVAL (N=3,301) and expression QTLs (eQTLs) from the eQTLGen Consortium (N=31,684) were used as genetic proxies for protein and mRNA expression levels. Two-sample MR of mRNA/protein expression on CRC risk was performed using eQTL/pQTL data combined with CRC genetic summary data from the Colon Cancer Family Registry (CCFR), Colorectal Transdisciplinary (CORECT), Genetics and Epidemiology of Colorectal Cancer (GECCO) consortia and UK Biobank (55,168 cases and 65,160 controls). ResultsAltered expression was detected for 125/5886 proteins. Of these, aspirin decreased MCM6, RRM2 and ARFIP2 expression and MR analysis showed that a standard deviation increase in mRNA/protein expression was associated with increased CRC risk (OR:1.08, 95% CI:1.03-1.13, OR:3.33, 95% CI:2.46-4.50 and OR:1.15, 95% CI:1.02-1.29, respectively). ConclusionMCM6 and RRM2 are involved in DNA repair whereby reduced expression may lead to increased DNA aberrations and ultimately cancer cell death, whereas ARFIP2 is involved in actin cytoskeletal regulation indicating a possible role in aspirins reduction of metastasis. ImpactOur approach has shown how laboratory experiments and population-based approaches can combine to identify aspirin-targeted proteins possibly affecting CRC risk.

cancer biology↗

bioRxiv2019

A new colorectal cancer risk prediction model incorporating family history, personal and environmental factors

PurposeReducing colorectal cancer (CRC) incidence and mortality through early detection would improve efficacy if targeted. A CRC risk-prediction model incorporating personal, family, genetic and environmental risk factors could enhance prediction.\n\nMethodsWe developed risk-prediction models using population-based CRC cases (N=4,445) and controls (N=3,967) recruited by the Colon Cancer Family Registry Cohort (CCFRC). A familial risk profile (FRP) was calculated to summarize individuals risk based on their CRC family history, family structure, germline mutation probability in major susceptibility genes, and a polygenic component. Using logistic regression, we developed risk models including individuals FRP or a binary CRC family-history (FH), and risk factors collected at recruitment. Model validation used follow-up data for population-(N=12,052) and clinic-based (N=5,584) relatives with no cancer history at recruitment, assessing calibration (E/O) and discrimination (AUC).\n\nResultsThe E/O (95% confidence interval [CI]) for FRP models for population-based relatives were 1.04 (0.74-1.45) and 0.86 (0.64-1.20) for men and women, and for clinic-based relatives 1.15 (0.87-1.58) and 1.04 (0.76-1.45). The age-adjusted AUC (95% CI) for FRP models in population-based relatives were 0.69 (0.60-0.78) and 0.70 (0.62-0.77), and for clinic-based relatives 0.77 (0.69-0.84) and 0.68 (0.60-0.76). The incremental values of AUC (95% CI) for FRP over FH models for population-based relatives were 0.08 (0.01-0.15) and 0.10 (0.04-0.16), and for clinic-based relatives 0.11 (0.05-0.17) and 0.11 (0.06-0.17).\n\nConclusionThe FRP-based model and FH-based model calibrate well in both settings. The FRP-based model provided better risk-prediction and discrimination than the FH-based model. A detailed family history may be useful for targeted risk-based screening and clinical management.

epidemiology↗