The artificial intelligence-based model ANORAK improves histopathological grading of lung adenocarcinoma

The introduction of the International Association for the Study of Lung Cancer grading system has furthered interest in histopathological grading for risk stratification in lung adenocarcinoma. Complex morphology and high intratumoral heterogeneity present challenges to pathologists, prompting the development of artificial intelligence (AI) methods. Here we developed ANORAK (pyrAmid pooliNg crOss stReam Attention networK), encoding multiresolution inputs with an attention mechanism, to delineate growth patterns from hematoxylin and eosin-stained slides. In 1,372 lung adenocarcinomas across four independent cohorts, AI-based grading was prognostic of disease-free survival, and further assisted pathologists by consistently improving prognostication in stage I tumors. Tumors with discrepant patterns between AI and pathologists had notably higher intratumoral heterogeneity. Furthermore, ANORAK facilitates the morphological and spatial assessment of the acinar pattern, capturing acinus variations with pattern transition. Collectively, our AI method enabled the precision quantification and morphology investigation of growth patterns, reflecting intratumoral histological transitions in lung adenocarcinoma

Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA

Circulating tumour DNA (ctDNA) can be used to detect and profile residual tumour cells persisting after curative intent therapy1. The study of large patient cohorts incorporating longitudinal plasma sampling and extended follow-up is required to determine the role of ctDNA as a phylogenetic biomarker of relapse in early-stage non-small-cell lung cancer (NSCLC). Here we developed ctDNA methods tracking a median of 200 mutations identified in resected NSCLC tissue across 1,069 plasma samples collected from 197 patients enrolled in the TRACERx study2. A lack of preoperative ctDNA detection distinguished biologically indolent lung adenocarcinoma with good clinical outcome. Postoperative plasma analyses were interpreted within the context of standard-of-care radiological surveillance and administration of cytotoxic adjuvant therapy. Landmark analyses of plasma samples collected within 120 days after surgery revealed ctDNA detection in 25% of patients, including 49% of all patients who experienced clinical relapse; 3 to 6 monthly ctDNA surveillance identified impending disease relapse in an additional 20% of landmark-negative patients. We developed a bioinformatic tool (ECLIPSE) for non-invasive tracking of subclonal architecture at low ctDNA levels. ECLIPSE identified patients with polyclonal metastatic dissemination, which was associated with a poor clinical outcome. By measuring subclone cancer cell fractions in preoperative plasma, we found that subclones seeding future metastases were significantly more expanded compared with non-metastatic subclones. Our findings will support (neo)adjuvant trial advances and provide insights into the process of metastatic dissemination using low-ctDNA-level liquid biopsy

Processed pseudogenes acquired somatically during cancer development

Contains fulltext : 136602.pdf (publisher's version ) (Open Access)Cancer evolves by mutation, with somatic reactivation of retrotransposons being one such mutational process. Germline retrotransposition can cause processed pseudogenes, but whether this occurs somatically has not been evaluated. Here we screen sequencing data from 660 cancer samples for somatically acquired pseudogenes. We find 42 events in 17 samples, especially non-small cell lung cancer (5/27) and colorectal cancer (2/11). Genomic features mirror those of germline LINE element retrotranspositions, with frequent target-site duplications (67%), consensus TTTTAA sites at insertion points, inverted rearrangements (21%), 5' truncation (74%) and polyA tails (88%). Transcriptional consequences include expression of pseudogenes from UTRs or introns of target genes. In addition, a somatic pseudogene that integrated into the promoter and first exon of the tumour suppressor gene, MGA, abrogated expression from that allele. Thus, formation of processed pseudogenes represents a new class of mutation occurring during cancer development, with potentially diverse functional consequences depending on genomic context

Segregation models

Many antigen receptors of the immune system belong to the family of multichain immune recognition receptors (MIRRs). Binding of ligand (antigen) to MIRR results in receptor phosphorylation, triggering downstream signaling pathways and cellular activation. How ligand binding induces this phosphorylation is not yet understood. In this Chapter, we discuss two models exploring the possibility that kinases and phosphatases are intermingled on the cell surface. Thus, in resting state, MIRR phosphorylation is counteracted by dephosphorylation. Upon ligand binding, phosphatases are removed from the vicinity of the MIRR and kinases, such that phosphorylated MIRRs can accumulate (segregation models). In the first model, clustering of MIRRs by multivalent ligand leads to their concentration in lipid rafts where kinases, but not phosphatases, are localized. The second model takes into account that the MIRR-ligand pair needs dose apposition of the two cell membranes, in cases where ligand is presented by an antigen-presenting cell. The intermembrane distance is too small to accommodate transmembrane phosphatases, which possess large ectodomains. Thus, phosphatases become spatially separated from the MIRRs and kinases (kinetic-segregation model)

Trajectory of cartilage loss within 4 years of knee replacement – a nested case–control study from the Osteoarthritis Initiative

ObjectiveKnee replacement (KR) represents a clinically important endpoint of knee osteoarthritis (KOA). Here we examine the 4-year trajectory of femoro-tibial cartilage thickness loss prior to KR vs non-replaced controls.MethodsA nested case-control study was performed in Osteoarthritis Initiative (OAI) participants: Cases with KR between 12 and 60 month (M) follow-up were each matched with one control (without KR through 60M) by age, sex, and baseline radiographic stage. Femoro-tibial cartilage thickness was measured quantitatively using magnetic resonance imaging (MRI) at the annual visit prior to KR occurrence (T0), and at 1-4 years prior to T0 (T-1 to T-4). Cartilage loss between cases and controls was compared using paired t-tests and conditional logistic regression.ResultsOne hundred and eighty-nine knees of 164 OAI participants [55% women; age 64 ± 8.7; body mass index (BMI) 29 ± 4.5] had KR and longitudinal cartilage data. Comparison of annualized slopes of change across all time points revealed greater loss in the central medial tibia (primary outcome) in KRs than in controls [94 ± 137 vs 55 ± 104 μm; P = 0.0017 (paired t); odds ratio (OR) 1.36 (95% confidence interval (CI): 1.08-1.70)]. The discrimination was stronger for T-2 → T0 [OR 1.61 (1.33-1.95), n = 127] than for T-1 → T0, and was not statistically significant for intervals prior to T-2 [i.e., T-4 → T-2, OR 0.97 (0.67-1.41), n = 60]. Results were similar for total medial femoro-tibial cartilage loss (secondary outcome), and when adjusting for pain and BMI.ConclusionsIn knees with subsequent replacement, cartilage loss accelerates in the 2 years, and particularly in the year prior to surgery, compared with controls. Whether slowing this cartilage loss can delay KR remains to be determined