Artificial Intelligence (AI) can be a useful tool in the management of disease processes such as hepatocellular carcinoma (HCC) as treatment decisions are often complex and multifaceted. AI applications in medicine are expanding with the ongoing advances in AI including more sophisticated machine learning and deep learning processes. In preliminary studies, AI algorithms have demonstrated superiority in predicting the development of HCC compared with standard models. Radiomics, a quantitative method used to extract features from medical imaging, has been applied to numerous liver imaging modalities to aid in the diagnosis and prognostication of HCC. Deep learning methodologies can help us to identify patients at higher likelihood of disease progression and improve risk stratification. AI applications have expanded into the field of surgery as models not only help us to predict surgical outcomes but AI methodologies are also used intra-operatively, in real time, to help us to define anatomic structures and aid in the resection of complex lesions. In this review, we discuss promising applications of AI in the management of HCC. While further clinical validation is warranted to improve generalizability through the inclusion of larger and more diverse populations, AI is expected to play a central role in assisting clinicians with the management of complex disease processes such as HCC.

Immune checkpoint blockade for the treatment of malignancies has been focused on reversing inhibitory pathways in T lymphocytes. NK cells are a potent innate defense against tumors and virally infected cells, but their therapeutic manipulation for anticancer immunity has been inadequately explored. Considerable attention has been focused on approaches to blocking inhibitory receptors on NK and myeloid cells. Most effort has been directed to the killer immunoglobulin-like receptors and CD94/NKG2A on NK cells. Another set of receptors with similar function in both NK cells and myeloid cells is the leukocyte immunoglobulin-like receptors (LILR) that interact with a wide variety of HLA molecules. Using pan–anti-HLA mAbs that recognize a conserved epitopic region on HLA also seen by LILRs, we investigated their functional effects in several models of tumor immunity. The pan–anti-HLA mAbs blocked the binding of most LILRs and did not block killer cell immunoglobulin-like receptors or CD94/NKG2A/C or T-cell receptor recognition. They also activated dysfunctional NK cells explanted from a variety of human cancers and resulted in enhancement of tumor immunity in humanized mice. The mAbs also exert direct antitumor effects. These results suggest that activation of innate immunity via disruption of HLA/LILR interactions is a potent approach for control of both primary tumors and potentially tumor metastases.

Given the propensity of aggressive epithelial tumors to form hepatic metastases, we performed an in vivo cDNA screen using the mouse liver and KRASG12D/TP53R273H pancreatic cells that identified the RNA-binding protein GCN1 as an integral component of hepatic outgrowth. RNAi experiments reveal that GCN1 triggers the integrated stress response (ISR) to activate serine, folate, and methionine biosynthetic pathways together with amino acid transporters, which act in concert to facilitate acquisition of metabolites and to restore redox homeostasis. Alongside the activation of the ISR, we found that GCN1 also functions in the nucleus where it interacts with HNRNPK to suppress the expression of MHC-I molecules and NK ligands. Intriguingly, we identified IMPACT as an endogenous competitive inhibitor of GCN1 that blocks both ISR-dependent metabolic control and disrupts HNRNPK interaction. In doing so, IMPACT enhances tumor immunogenicity to unleash NK cell killing, in addition to sensitizing metastatic tumor cells to immune checkpoint blockade. Significance: Metastatic tumor cells display profound immunometabolic plasticity to colonize distant organs. We identify IMPACT, an inhibitor of GCN1-stress signaling, expression of which curtailed metabolic plasticity and augmented tumor immunogenicity, sensitizing metastatic tumor cells to NK cell–mediated destruction.

Objective: This study examines the success of surgeon-scientists compared with nonsurgeon physician-scientists in obtaining National Institutes of Health (NIH) funding after participation in a research training grant. Background: Dedicated research time during postgraduate training for physician-scientists is advantageous for obtaining future independent funding from NIH. Methods: NIH Reporter was used to identify F32 and T32 grants awarded to internal medicine and surgery departments from 2005 to 2015, and an internal NIH database was used to determine funding outcomes. Success rates were recorded for surgeon versus internist PIs who applied for either a mentored career grant or research project grant (RPG). The median time in years from the final year of the training grant and clinical graduation to the first awarded grant was investigated. χ ² tests, Fisher exact tests, and Wilcoxon rank sum tests were used. Results: A greater proportion of surgeons transitioned directly to an RPG, 27% (68 internist PIs) compared with 72% (63 surgeon PIs) ( P <0.001). Both T32 and F32 trained surgeons were able to obtain an RPG sooner than internists, taking a median of 5 years from the end of clinical training versus a median of 7 years for internists [ P =0.033 (F32), P =0.034 (T32)]. Conclusions: Although fewer F32 and T32-funded surgeons apply for subsequent NIH funding compared with nonsurgeons, more surgeons apply for an RPG instead of a K-grant. Remarkably, surgeons obtained independent funding sooner after clinical graduation compared with internists, despite the extensive gap in time between postgraduate training and first faculty appointment, an amazing accomplishment given their clinical training and surgical practice challenges.

PURPOSE: Most patients with metastatic colorectal cancer (CRC) have microsatellite stable or mismatch repair-proficient tumors, which are resistant to immunotherapy especially in cases of liver metastases. We sought to determine whether tumor-targeted interleukin-12 (PDS01ADC) can improve outcomes for patients with CRC liver metastases managed with hepatic artery infusion pump (HAIP) chemotherapy. MATERIALS AND METHODS: NCT05286814 is a phase II nonrandomized trial evaluating subcutaneous PDS01ADC in combination with HAIP floxuridine and systemic chemotherapy (leucovorin, 5-fluorouracil, and oxaliplatin or leucovorin, 5-fluorouracil, and irinotecan) in patients with unresectable microsatellite stable or mismatch repair-proficient colorectal liver metastases previously treated with at least one line of systemic chemotherapy. The primary end points for the planned interim analysis were overall response rate and safety. RESULTS: Nine patients were included in this planned interim analysis. Seventy-eight percent (7/9) of patients receiving PDS01ADC with HAIP therapy had partial or complete responses at 6 months. The median hepatic progression-free survival for patients receiving PDS01ADC + HAIP therapy was 12.7 months with a minimum follow-up of 13.1 months. Grade ≥3 toxicities occurred in 78% but were manageable and did not limit HAIP therapy. No patients developed a biliary stricture within 6 months of initiating treatment. Clinical responders to PDS01ADC demonstrated enhanced peripheral immune activation, including elevated levels of circulating T-cell subsets with stem-like features, and increased CD8 ⁺ T-cell:T regulatory cell ratio in tissue biopsies. CONCLUSION: Addition of PDS01ADC is not detrimental to HAIP therapy and is associated with both systemic and intratumoral immune modulation. Initial results warrant continuation to full enrollment for further evaluation of clinical and scientific end points.

Recent studies report a decrease in R01 grants awarded to surgeon-scientists compared to nonsurgeons. We determined the key factors associated with a successful R01 grant application for surgeon-scientists. Surgeon-scientist principal new investigators (PIs) who applied for an R01 grant during fiscal years (FY) 2018-2023 were identified using an National Institutes of Health internal data platform. Individual and multivariable analyses were performed for gender, degree (medical degree with or without PhD), previous research training grants (F32 and T32), same faculty and clinical training institution, previous mentored funding (K08, K23, and K99), and Hirsch index for awarded and nonawarded PIs. Preliminary analyses were conducted to explore associations between the R01 award and each variable followed by a multiple logistic regression analysis. Of 310 (35.1%) R01-awarded surgeon PIs, there was no statistical difference in the proportion of awarded men (n = 203, 34.5%) versus women (n = 107, 36.5%) PIs (P = 0.55). The results indicated a strong likelihood of success for PIs with a PhD degree (univariable P = 0.007; odds ratio (OR) = 1.39, P = 0.042 by the logistic model), for those who were previously on an F32 or T32 training grant (P = 0.008; OR = 1.51, P = 0.025), and were previously awarded a mentored-career grant (K08, K23, or K99) (P < 0.0001; OR = 2.72, P < 0.0001). In contrast, remaining at the same organization as their surgical training (P = 0.069; OR = 1.27, P = 0.109), and an h-index ≥40 (P = 0.183; OR = 1.34, P = 0.184) were not indicators of success. Variables identified for successfully transitioning to independent R01 as first investigator surgeon scientist funding include holding a PhD degree, a previous research training grant, and a previous mentored career award.