Hohenstein, Jessica D.

CTNNB1- mutated hepatocellular carcinomas are characterized by a distinctive morphology and activation of the Wnt pathway. AXIN1 also plays a key role in the Wnt pathway, but the morphology of AXIN1-mutated tumors has not been examined. In addition, there are ongoing questions on the ability of AXIN1 mutations to activate the Wnt pathway in hepatocellular carcinoma. AXIN1 mutated tumors (N=18) were studied, along with control groups: CTNNB1 (N=17), APC (6), or “Other” genes in the Wnt pathway (5). Wnt pathway activation was studied by immunostains for beta-catenin and glutamine synthetase. Findings were supplemented by gene expression analysis using TCGA data. On histologic examination, the classic morphology associated with beta-catenin mutations was found in all 4 groups: 8/18 AXIN1 (44%), 10/17 CTNNB1 (59%), 4/6 APC (67%), and 1/5 Other (20%). By immunohistochemistry, Wnt pathway activation was found in 11/18 AXIN1 (61%), 15/17 CTTNB1 (88%), 6/6 APC (100%), and 5/5 (100%) of Other. In AXIN1- mutated tumors, the Wnt pathway was weakly activated. Glutamine synthetase stains also highlighted a new “progressed pattern” associated with distinct subnodules of staining. Tertiary lymphoid structures were uncommon except for cases with CTTNNB1 mutations plus additional mutations in the Wnt pathway. In summary, the classic morphology associated with CTNNB1 mutations is found in hepatocellular carcinomas with mutations in AXIN1 , APC , and other Wnt genes. AXIN1 mutated tumors have Wnt activation that is detectable but at lower levels than CTNNB1 mutated tumors. As tumors progress, their level of Wnt activation can change.

ABSTRACT Periprosthetic joint infection (PJI) is the most common and difficult to treat form of arthroplasty failure. While treatment with debridement, antibiotics, and implant retention (DAIR) is preferable to one- or two-stage implant exchange based on morbidity and cost, outcomes are not successful in all cases selected for this management strategy. DAIR is currently recommended when infection is perceived to be in an “acute” phase, based on symptom duration; despite this selection strategy, DAIR failure rates are high. A more objective means of predicting DAIR success could improve patient outcomes by limiting DAIR failures. To explore this possibility, advanced proteomic analysis of sonicate fluid samples from 95 subjects with PJI was performed using proximity extension assay (PEA), with 77 samples additionally undergoing complementary proteomics analysis with liquid chromatography with tandem mass spectrometry (LC-MS/MS). Sparse partial least squares differentiation analysis (sPLS-DA) separated samples from patients who underwent DAIR with known outcomes ( n = 19) into successful or unsuccessful groups, predicting DAIR surgical outcome (area under the curve [AUC]: 1; mean “leave one out” AUC: 0.6). Proteins predictive of DAIR surgical outcome were significantly enriched for the “protein repair” Gene Ontology (GO) pathway ( P -adj = 0.02). Additionally, proteomic signatures associated with symptom duration in PJI categorized samples into short and long symptom duration PJI. In summary, an investigation of 7,261 unique human proteins separated PJI-associated samples based on symptom duration and identified a proteomic profile predictive of DAIR success. IMPORTANCE Chronic infections are generally understood to last months to years, with acute infections lasting days to weeks. The transition from acute to chronic infection is, however, poorly understood. Periprosthetic joint infection (PJI) has been considered more challenging to treat when “chronic” than when “acute.” A surgery preferred for its recovery time and cost—debridement, antibiotics, and implant retention (DAIR)—is recommended for PJI management when symptom duration is short; yet, even in this select patient group, DAIR is associated with a high treatment failure rate. A means to better identify those predicted to have a successful outcome if they undergo DAIR is needed. Here, over 7,000 proteins from human clinical PJI samples were measured and shown to be able to separate samples based on symptom duration. Importantly, a proteomic profile predictive of DAIR success was identified.