Citations

A new systems approach to diseased states and wellness result in a new branch in the healthcare services, namely, Personalized and Precision Medicine (PPM). To achieve the implementation of PPM concept, it is necessary to create a fundamentally new strategy based upon the recogni-tion of biomarkers and thus the targets to secure the grand future of drug design and drug dis-covery.Each decision-maker values the impact of their decision to use PPM on their own budget and well-being, which may not necessarily be optimal for society as a whole. It would be extremely useful to integrate data harvesting from different databanks for applications to provide more tai-lored measures for the patients resulting in improved patient outcomes, reduced adverse events, and more cost-effective use of the latest health care resources including diagnostic (companion ones or theranostics), preventive and therapeutic (targeted molecular and cellular) etc.Meanwhile, along with the impact of genomics and bioinformatics, pathology is the central specialty of PPM-related resources. Coupled with IT, the upgraded tools are ever more efficient and robust within clinical cancer settings. The latest algorithms may be able to identify and vali-date patterns which humans are not capable of quantifying easily, such as slight differences in textures or morphologies. In this sense, the impact of pathology allows a modular approach, as its various aspects are under development in several areas of PPM.Among the above-mentioned medical specialists involved in PPM, the pathologists play an im-portant and key role in the implementation and development of PPM-driven resources that are in the center of decision of many therapeutic choices. Recent advances in systems biology have tremendously affected the practice of precision pathology, gradually transforming it from a morphology-based into a precise molecular-based discipline. The enormous development of precision pathology research (integrating molecular OMICS and digital approaches) has raised great expectations concerning its impact on PPM aiming to custom-ize medical practice with a focus on the individual, based on the use of molecular tests, identifi-cation of genomic biomarkers, and development of targeted drugs.The precision pathology process introduces a new paradigm in pathology by leveraging digital imaging and IT technologies, and provides significant advancements in accuracy, efficiency, and collaboration. Among the latest innovations the precision pathology supported by digital tools, would dictate the implementation of high-resolution imaging, image analysis tools and integra-tion with molecular OMICS data. Integration of the approaches and resources will provide a true challenge for the future, requiring collaboration between oncologists, pathologists, biodesigners and bioengineers and remaining a challenge to precision cancer practice and profiled bioindustry.The latter requires precision pathologists highly trained in pre-analytic processes, tumor area mi-crodissection for tumor cell enrichment, methodology analysis and results. The in-depth study of molecular alterations in patients allows optimizing molecular diagnosis and selecting candidates for receive novel treatments against specific molecular targets. These patients would benefit from multidisciplinary approach and learning. In this sense, molecular diagnostics has a long tradition in pathology, especially in clinical one, where various OMICS-analyses of cancers are incorpo-rated into diagnostic and decision-making algorithms to secure a way where the pathologists con-tinue to play an essential role in developing and implementing molecular profiling tests in practice and communicate the results and their relevance with cancer practitioners.Cancer pathology is the central specialty of personalized and precision oncology (PPO). Meanwhile, the combination of comprehensive biobanking and the next wave of theranostic pathology technologies provides a natural, externally visible infrastructure that now allows pa-thology as a discipline – to engage directly with the biotechnology and pharma sector. We’re at an exciting junction in precision cancer pathology’s growth as a medical specialty, and pathology-driven biobanking is becoming both central to our core expertise and, even more importantly, a powerful enabler for many of the most promising growth areas of our discipline: PPM healthcare, clinical trials and drug development, theranostics, and functional assessment and monitoring of disease. In the context of these changes and challenges, the precision cancer pathology can play a fundamental role in both PPO-guided clinical practice and biodesign-driven cancer research.

Abstract Context Incidental thyroid findings (ITFs) are increasingly detected on imaging performed for non-thyroid indications. Their prevalence, features, and consequences remain undefined. Objective To develop, validate, and deploy a natural language processing (NLP) pipeline to identify ITFs in radiology reports and assess their prevalence, features, and clinical outcomes. Design Retrospective cohort study. Setting Mayo Clinic sites (Rochester, Arizona, Florida, Mayo Clinic Health System). Participants Adults without prior thyroid disease undergoing thyroid-capturing imaging from July 1, 2017, to September 30, 2023. A transformer-based NLP pipeline identified ITFs and extracted nodule characteristics from image reports from multiple modalities and body regions. Outcomes ITF prevalence, downstream thyroid ultrasound, biopsy, thyroidectomy, and cancer diagnosis. Logistic regression identified demographic and imaging-related factors. Results Among 115 683 patients (mean age, 56.8 [SD 17.2]; 52.9% women), 9077 (7.8%) had an ITF (92.9% nodular). ITFs were more likely in women, older adults, higher BMI, and in imaging ordered by specialties different from Emergency Medicine. Compared with chest CT, ITFs were more likely via neck CT, PET, and nuclear medicine scans. Nodule characteristics were poorly documented, with size reported in 44% and other features in fewer than 15%. Compared with patients without ITFs, those with ITFs had higher odds of thyroid nodule diagnosis (OR 45, 95%CI 41.1-49.3), biopsy (OR 46.8, 95%CI 39.0-56.2) thyroidectomy (OR 55.8, 95%CI 31.3-99.3), and thyroid cancer diagnosis (OR 61.7, 95%CI 38.6-98.5). Most cancers were papillary (88.5%) and larger when detected after ITFs (2 cm SD 1.4) vs no ITF (1.3 cm SD 0.8). Conclusion ITFs were common and strongly associated with cascades leading to the detection of small, low-risk cancers, highlighting their role in overdiagnosis and the need for standardized reporting and more selective follow-up.

Abstract Pancreatic cancer disproportionately affects Black individuals in the United States, but they have limited representation in genetic studies of pancreatic ductal adenocarcinoma (PDAC). To address this gap, we performed admixture mapping and genome-wide association analysis (GWAS) in genetically inferred African ancestry individuals (1,030 cases and 889 controls). Admixture mapping identified three regions with a significantly higher proportion of African ancestry in cases compared to controls (5q33.3, 10p1, 22q12.3). GWAS identified a genome-wide significant association at 5p15.33 ( CLPTM1L , rs383009:T>C, T Allele Frequency=0.51, OR:1.45, P value=1.24×10 -8 ), a locus previously associated with PDAC. Known loci at 5p15.33, 7q32.3, 8q24.21 and 7q25.1 also replicated (P value <0.01). Multi-ancestral fine-mapping identified two potential causal SNPs (rs3830069 and rs2735940) at 5p15.33. Collectively these findings identified novel PDAC risk loci and expanded our understanding of this deadly cancer in underrepresented populations, emphasizing the multifactorial nature of PDAC risk including inherited genetic and non-genetic factors. Statement of Significance To understand how genetic variation contributes to PDAC risk in Black people in North American, we studied individuals of genetically-inferred African ancestry. We identified novel risk loci and differences in the contribution of known loci. This demonstrates that ancestry-informed genetic analyses improve our understanding of PDAC risk and enhances discovery.

Abstract Solitary bone plasmacytoma (SBP) and SBP with minimal marrow involvement (SBPmm) are treated similarly with definitive radiation therapy (RT) followed by observation. However, differences in the natural disease course after RT between the two, are not well described. We performed a multicenter study assessing outcomes after RT in 141 patients with SBP and 102 with SBPmm diagnosed between January 2010 and December 2024. About 92% of patients with SBPmm progressed to multiple myeloma (MM) vs 76% of those with SBP (P = .01). Among patients with SBP, 21% progressed with a second solitary bone lesion vs 4% with SBPmm (P&lt; .01). Patients with longer time to progression (TTP) after initial RT could achieve durable responses with RT to a second solitary plasmacytoma in the absence of other myeloma-defining events (MDE). Multifocal lytic bone lesions were the most common MDE, occurring in 89% and 81% of patients with SBPmm and SBP, respectively. Patients with SBPmm had a median TTP of 15 months (95% confidence interval [CI], 14-21) compared to 43 months (95% CI, 34-55) for those with SBP (P&lt; .0001); 67% with SBPmm progressed within 2 years of diagnosis. Del(17p) and 1q+ (gain or amplification) were associated with shorter TTP to MM in SBPmm, with 2-year progression rates of 100% and 82%, respectively. We report significant differences in risk and modes of progression between SBP and SBPmm. Patients with SBPmm are at particularly high risk for early progression to MM, with most developing bone disease as the MDE. These findings support prospective studies incorporating frontline systemic therapy for SBPmm.

Enteroblastic, hepatoid, and clear cell carcinomas are rare subtypes of colorectal carcinoma (CRC) with histologic and immunohistochemical (IHC) overlap. We assessed 37 CRCs that possibly represent these subtypes. Provisional criteria for each subtype, along with case photomicrographs and IHC data, were circulated among the authors to provide diagnostic interpretations. Based on plurality consensus, the carcinomas were classified as enteroblastic (n=13), hepatoid (n=6), and clear cell (n=18). Unanimous agreement was reached in 18% (3 clear cell, 3 hepatoid). Interobserver analysis revealed a mean pairwise Cohen κ of 0.63 (range: 0.32 to 0.91), with the hepatoid subtype eliciting the greatest consensus. Clear cell areas were the most likely to intermix with areas of conventional CRC ( P <0.001). Seven patients (20%) had inflammatory bowel disease (mostly linked to enteroblastic CRC). Twenty-three of 34 patients (68%) had nodal metastasis, and 12 (32%) had distant metastasis (mostly to the liver) at presentation. Median recurrence-free survival was 17 months, with enteroblastic cases the most likely to recur (54%, P =0.015). Median follow-up length was 27 months, with 14 patients (40%) dying of disease (representing 7 enteroblastic, 4 hepatoid, and 3 clear cell CRC). Mutations were identified in TP53 (n=8) , APC (n=3) , FBXW7 (n=2), and KRAS (n=1). Inflammatory bowel disease significantly worsened recurrence-free survival on multivariate analysis, while distant metastasis significantly worsened both recurrence-free and overall survival on multivariate analysis. Enteroblastic, hepatoid, and clear cell CRC demonstrate morphologic and IHC overlap, leading to interobserver variability in diagnosis. Given potential differences in clinical correlations and outcomes, more refined criteria are likely necessary.

Abstract Alzheimer’s disease (AD) emerges from multi-scale interactions between molecular pathology and disruptions in large-scale brain network dynamics. Understanding how these processes co-evolve and relate to disease stages is essential for advancing complex systems models of aging and AD, and for developing system-informed interventions. However, progress has been limited by a lack of large-scale longitudinal data. To address this, we examined the longitudinal relationship between subsystems of the default mode network (DMN) (posterior DMN, ventral DMN, anterior dorsal DMN) using task-free functional MRI (fMRI) and amyloid positron emission tomography (PET) imaging in a large longitudinal cohort spanning the clinico-biological spectrum of AD (n = 1,451; 2,763 time points) using mixed-effect models. We also assessed whether patterns of DMN connectivity predicted conversion to amyloid positivity, mild cognitive impairment (MCI), and dementia using Cox proportional hazards models. Our findings reveal a dynamic interplay between amyloid accumulation and connectivity within and between DMN subsystems, with both hyper- and hypoconnectivity emerging across DMN subsystems in association with increasing amyloid burden. Importantly, survival models showed that DMN connectivity patterns predicted conversion to critical stages of the disease, including not only conversion to MCI and dementia, but also conversion to amyloid positivity in otherwise clinically unimpaired individuals who were amyloid negative at baseline. These associations were independent of age, APOE4 status, sex, education, and in-scanner motion. These results support a model in which breakdowns in tightly regulated feedback loops governing DMN physiology represent a core systems-level pathophysiology of AD. Notably, this functional dyshomeostasis precedes detectable amyloidosis on imaging. Future studies should focus on the development of robust biomarkers of brain function that can be applied at the individual level, which could in turn help support the development of therapeutic approaches targeting system-level pathophysiology.

Abstract Skin biopsies analyzed with α-synuclein seed amplification assays (SAAs) are a simple way to clinically interrogate the presence of α-synuclein aggregates. We determined the accuracy of skin biopsy SAA in predicting the clinical diagnoses of Parkinson disease (PD), PD with dementia (PDD) and dementia with Lewy bodies (DLB). Blinded SAAs were performed in 3 independent laboratories. Subjects diagnosed with PD, PDD and DLB were analyzed together as group 1, clinically unaffected subjects as group 2 and those with risk factors for LBD as group 3. Punch biopsies were taken from the posterior neck and analyzed by the 3 labs in 6 separate SAAs. Pairwise agreement between labs and assays ranged from excellent (kappa 0.82) to moderate (kappa 0.40-0.68). Sensitivity across assays ranged between 50.0% and 61.3%; specificity ranged between 68.6% and 100%. Comparisons of group 1 vs group 2 produced the greatest specificities, between 77.3% and 100%. In 17 cases that subsequently came to autopsy, 93% of SAAs were positive in those at the neocortical LBD stage but in only &lt;10% of those at lower stages. Skin biopsy α-synuclein SAA may be useful as a diagnostic and progression biomarker in Lewy body dementia clinical trials.

ABSTRACT Circulating tumor DNA (ctDNA) as a liquid biopsy is an emerging tool used for diagnosis and disease monitoring, yet not all tumors shed DNA equally, thus currently limiting the clinical applicability of this tool. Our institution has developed and validated a droplet digital Polymerase Chain Reaction (ddPCR) ctDNA test for BRAF V600 mutation. We collected data on all BRAF mutated melanoma patients tested with the ddPCR BRAF assay at our institution over the years 2018–2024 and correlated the test results with clinical and radiological baseline parameters, with a focus on Positron Emission Tomography‐Computed Tomography (PET‐CT) data, incorporating both location of lesions and volume of disease. Linear and logistic regression modelling was used to assess possible associations between the baseline parameters and the ctDNA results. We identified 71 BRAF mutated melanoma patients, of which 65 had active disease on imaging studies and 43 had PET‐CT data available for analysis. Multivariate modelling has shown that patients were more likely to have a positive ctDNA result if they had elevated serum lactate dehydrogenase (LDH) (OR = 9.9), had a higher number of lesions on imaging studies (> 10 lesions: OR = 11.3), and if they were younger than 65 (OR = 11.8), with an AUC of 0.84. The PET‐CT calculated total metabolic tumor volume correlated with the quantitative ctDNA result with a Pearson r factor of 0.49. In conclusion, ctDNA ddPCR BRAF testing is easily obtained and might be especially beneficial for patients diagnosed with a clinically aggressive disease, based on elevated LDH, higher PET‐CT metabolic tumor volume, and younger age.