MATERIALS AND METHODS: This retrospective study involved archival search of patients with GI biopsies that showed eosinophilic infiltration from January 2004 to December 2012. Patients' clinical data from computerised hospital records and clinical notes was reviewed. Diagnostic criteria for EG included presence of GI symptoms with more than 30 eosinophils/high power field on GI biopsies. Patients with secondary causes for eosinophilia were excluded.

RESULTS: Eighteen patients with EG were identified (mean age 52 years; male/female: 11/7). Fifteen patients (83%) had peripheral blood eosinophilia. Seven patients (39%) had atopic conditions. Most common symptoms were diarrhoea and abdominal pain. Small intestine was the most common site involved. Endoscopic finding was non-specific. Ten patients were treated with corticosteroids (nine prednisolone, one budesonide): eight patients (89%) responded clinically to prednisolone but four patients (50%) relapsed following tapering-off of prednisolone and required maintenance dose. One patient each responded to diet elimination and montelukast respectively. Half of the remaining six patients who were treated with proton-pump inhibitors, antispasmodic or antidiarrheal agents still remained symptomatic.

METHODS: Using multi-region sampled RNA-seq data of 90 patients, we performed patient-specific differential expression testing, together with the patients' matched adjacent normal samples.

RESULTS: Comparing the results from conventional DE analysis and patient-specific DE analyses, we show that the conventional DE analysis omits some genes due to high inter-individual variability present in both tumour and normal tissues. Dysregulated genes shared in small subgroup of patients were useful in stratifying patients, and presented differential prognosis. We also showed that the target genes of some of the current targeted agents used in HCC exhibited highly individualistic dysregulation pattern, which may explain the poor response rate.

METHODS: Through the Asia-Pacific Hepatocellular Carcinoma trials group (NCT03267641), we recruited one of the largest prospective cohorts of patients with HCC, with over 600 whole genome and transcriptome samples from 123 treatment-naïve patients.

RESULTS: Using a multi-region sampling approach, we revealed seven convergent genetic evolutionary paths governed by the early driver mutations, late copy number variations and viral integrations, which stratify patient clinical trajectories after surgical resection. Furthermore, such evolutionary paths shaped the molecular profiles, leading to distinct transcriptomic subtypes. Most significantly, although we found the coexistence of multiple transcriptomic subtypes within certain tumors, patient prognosis was best predicted by the most aggressive cell fraction of the tumor, rather than by overall degree of transcriptomic ITH level - a phenomenon we termed the 'bad apple' effect. Finally, we found that characteristics throughout early and late tumor evolution provide significant and complementary prognostic power in predicting patient survival.

CONCLUSIONS: Taken together, our study generated a comprehensive landscape of evolutionary history for HCC and provides a rich multi-omics resource for understanding tumor heterogeneity and clinical trajectories.

IMPACT AND IMPLICATIONS: This prospective study, utilizing comprehensive multi-sector, multi-omics sequencing and clinical data from surgically resected hepatocellular carcinoma (HCC), reveals critical insights into the role of tumor evolution and intra-tumor heterogeneity (ITH) in determining the prognosis of HCC. These findings are invaluable for oncology researchers and clinicians, as they underscore the influence of distinct evolutionary paths and the 'bad apple' effect, where the most aggressive tumor fraction dictates disease progression. These insights not only enhance prognostic accuracy post-surgical resection but also pave the way for personalized treatment strategies tailored to specific tumor evolutionary and transcriptomic profiles. The coexistence of multiple subtypes within the same tumor prompts a re-appraisal of the utilities of depending on single samples to represent the entire tumor and suggests the need for clinical molecular imaging. This research thus marks a significant step forward in the clinical understanding and management of HCC, underscoring the importance of integrating tumor evolutionary dynamics and multi-omics biomarkers into therapeutic decision-making.