Background

A non-synonymous single nucleotide polymorphism of the ATG16L1 gene, T300A, is a major Crohn's disease (CD) susceptibility allele, and is known to be associated with increased apoptosis induction in the small intestinal crypt base in CD subjects and mouse models. We hypothesized that ATG16L1 T300A genotype also correlates with increased tumor apoptosis and therefore could lead to superior clinical outcome in cancer subjects.

Methods

T300A genotyping by Taqman assay was performed for gastric carcinoma subjects who underwent resection from two academic medical centers. Transcriptomic analysis was performed by RNA-seq on formalin-fixed paraffin-embedded cancerous tissue. Tumor apoptosis and autophagy were determined by cleaved caspase-3 and p62 immunohistochemistry, respectively. The subjects' genotypes were correlated with demographics, various histopathologic features, transcriptome, and clinical outcome.

Findings

Of the 220 genotyped subjects, 163 (74%) subjects carried the T300A allele(s), including 55 (25%) homozygous and 108 (49%) heterozygous subjects. The T300A/T300A subjects had superior overall survival than the other groups. Their tumors were associated with increased CD-like lymphoid aggregates and increased tumor apoptosis without concurrent increase in tumor mitosis or defective autophagy. Transcriptomic analysis showed upregulation of WNT/β-catenin signaling and downregulation of PPAR, EGFR, and inflammatory chemokine pathways in tumors of T300A/T300A subjects.

Interpretation

Gastric carcinoma of subjects with the T300A/T300A genotype is associated with repressed EGFR and PPAR pathways, increased tumor apoptosis, and improved overall survival. Genotyping gastric cancer subjects may provide additional insight for clinical stratification.

BACKGROUND: Artificial intelligence (AI) is rapidly fuelling a fundamental transformation in the practice of pathology. However, clinical integration remains challenging, with no AI algorithms to date in routine adoption within typical anatomic pathology (AP) laboratories. This survey gathered current expert perspectives and expectations regarding the role of AI in AP from those with first-hand computational pathology and AI experience. METHODS: Perspectives were solicited using the Delphi method from 24 subject matter experts between December 2020 and February 2021 regarding the anticipated role of AI in pathology by the year 2030. The study consisted of three consecutive rounds: 1) an open-ended, free response questionnaire generating a list of survey items; 2) a Likert-scale survey scored by experts and analysed for consensus; and 3) a repeat survey of items not reaching consensus to obtain further expert consensus. FINDINGS: Consensus opinions were reached on 141 of 180 survey items (78.3%). Experts agreed that AI would be routinely and impactfully used within AP laboratory and pathologist clinical workflows by 2030. High consensus was reached on 100 items across nine categories encompassing the impact of AI on (1) pathology key performance indicators (KPIs) and (2) the pathology workforce and specific tasks performed by (3) pathologists and (4) AP lab technicians, as well as (5) specific AI applications and their likelihood of routine use by 2030, (6) AIs role in integrated diagnostics, (7) pathology tasks likely to be fully automated using AI, and (8) regulatory/legal and (9) ethical aspects of AI integration in pathology. INTERPRETATION: This systematic consensus study details the expected short-to-mid-term impact of AI on pathology practice. These findings provide timely and relevant information regarding future care delivery in pathology and raise key practical, ethical, and legal challenges that must be addressed prior to AIs successful clinical implementation. FUNDING: No specific funding was provided for this study.

Pancreatitis is a complex, progressively destructive inflammatory disorder. Alcohol was long thought to be the primary causative agent, but genetic contributions have been of interest since the discovery that rare PRSS1, CFTR and SPINK1 variants were associated with pancreatitis risk. We now report two associations at genome-wide significance identified and replicated at PRSS1-PRSS2 (P < 1 × 10(-12)) and X-linked CLDN2 (P < 1 × 10(-21)) through a two-stage genome-wide study (stage 1: 676 cases and 4,507 controls; stage 2: 910 cases and 4,170 controls). The PRSS1 variant likely affects disease susceptibility by altering expression of the primary trypsinogen gene. The CLDN2 risk allele is associated with atypical localization of claudin-2 in pancreatic acinar cells. The homozygous (or hemizygous in males) CLDN2 genotype confers the greatest risk, and its alleles interact with alcohol consumption to amplify risk. These results could partially explain the high frequency of alcohol-related pancreatitis in men (male hemizygote frequency is 0.26, whereas female homozygote frequency is 0.07).

Pancreatitis is a complex, progressively destructive inflammatory disorder. Alcohol was long thought to be the primary causative agent, but genetic contributions have been of interest since the discovery that rare PRSS1, CFTR and SPINK1 variants were associated with pancreatitis risk. We now report two associations at genome-wide significance identified and replicated at PRSS1-PRSS2 (P < 1 × 10(-12)) and X-linked CLDN2 (P < 1 × 10(-21)) through a two-stage genome-wide study (stage 1: 676 cases and 4,507 controls; stage 2: 910 cases and 4,170 controls). The PRSS1 variant likely affects disease susceptibility by altering expression of the primary trypsinogen gene. The CLDN2 risk allele is associated with atypical localization of claudin-2 in pancreatic acinar cells. The homozygous (or hemizygous in males) CLDN2 genotype confers the greatest risk, and its alleles interact with alcohol consumption to amplify risk. These results could partially explain the high frequency of alcohol-related pancreatitis in men (male hemizygote frequency is 0.26, whereas female homozygote frequency is 0.07).