Background: Alpha-fetoprotein (AFP) and des-gamma carboxyprothrombin (DCP), also known as protein induced by vitamin K absence-II (PIVKA-II [DCP]) are biomarkers for HCC with limited diagnostic value when used in isolation. The novel GAAD algorithm is an in vitro diagnostic combining PIVKA-II (DCP) and AFP measurements, age, and gender (biological sex) to generate a semi-quantitative result. We conducted prospective studies to develop, implement, and clinically validate the GAAD algorithm for differentiating HCC (early and all-stage) and benign chronic liver disease (CLD), across disease stages and etiologies. Methods: Patients aged ≥18 years with HCC or CLD were prospectively enrolled internationally into algorithm development [n = 1084; 309 HCC cases (40.7% early-stage) and 736 controls] and clinical validation studies [n = 877; 366 HCC cases (47.6% early-stage) and 303 controls]. Serum samples were analyzed on a cobas^® e 601 analyzer. Performance was assessed using receiver operating characteristic curve analyses to calculate AUC. Results: For algorithm development, AUC for differentiation between early-stage HCC and CLD was 90.7%, 84.4%, and 77.2% for GAAD, AFP, and PIVKA-II, respectively. The sensitivity of GAAD for the detection of early-stage HCC was 71.8% with 90.0% specificity. Similar results were shown in the clinical validation study; AUC for differentiation between early-stage HCC and CLD was 91.4% with 70.1% sensitivity and 93.7% specificity. GAAD also showed strong specificity, with a lower rate of false positives regardless of disease stage, etiology, or region. Conclusions: The GAAD algorithm significantly improves early-stage HCC detection for patients with CLD undergoing HCC surveillance. Further phase III and IV studies are warranted to assess the utility of incorporating the algorithm into clinical practice.

We compared the clinical performance of the novel GAAD (gender [biological sex], age, alpha-fetoprotein [AFP], des-gamma carboxyprothrombin [DCP]) and GALAD (gender [biological sex], age, AFP, Lens culinaris agglutinin-reactive AFP [AFP-L3], DCP) algorithms to deduce the clinical utility of AFP-L3 for detecting early-stage hepatocellular carcinoma (HCC) from chronic liver disease (CLD). An algorithm development study (STOP-HCC-ARP) and clinical validation study (STOP-HCC-MCE) were conducted, recruiting adult participants with HCC (confirmed by radiology or pathology) or CLD in an international, multicenter, case-control design. Serum biomarkers were measured using Elecsys assays (GAAD and GALAD [Cobas]) or μTASWAKO assays (GALAD [μTASWAKO]) while blinded to case/control status. In STOP-HCC-ARP (algorithm development cohort), 1,006 patients {297 HCC (41.4% early-stage [Barcelona Clinic Liver Cancer {BCLC} 0/A) and 709 CLD} were included. Area under the curve (AUCs) for discriminating between early-stage HCC vs. CLD were 91.4%, 91.4%, and 90.8% for GAAD (Cobas), GALAD (Cobas), and GALAD (μTASWAKO), respectively. The clinical validation cohort of STOP-HCC-MCE comprised 1,142 patients, (366 HCC cases [48% early-stage], 468 specificity samples and 302 CLD); AUCs for GAAD (Cobas), GALAD (Cobas), and GALAD (μTASWAKO) for discriminating between early-stage HCC vs. CLD were 91.4%, 91.5%, and 91.0%, respectively; AUCs were 94.7–95.0% for all-stage HCC. The GAAD and GALAD algorithms demonstrated similar good performance regardless of disease etiology, presence of cirrhosis, geographical region, and within pan-tumor specificity panels (p <0.001). GAAD (Cobas) demonstrated good clinical performance, similar to GALAD (Cobas and μTASWAKO) algorithms, in differentiating HCC and CLD controls, across all disease stages, etiologies, and regions; therefore, AFP-L3 may have a negligible role in GALAD for HCC surveillance. To improve the detection of early-stage hepatocellular carcinoma (HCC) from benign chronic liver disease (CLD), algorithms combining demographic characteristics and serum biomarkers, such as GAAD and GALAD, have been developed. GAAD combines gender (biological sex), age, alpha-fetoprotein (AFP), des-gamma carboxy-prothrombin (DCP); GALAD combines the same characteristics and biomarkers as GAAD with the addition of Lens culinaris agglutinin-reactive AFP (AFP-L3). Changing disease etiologies and treatment paradigms have raised questions regarding the utility of AFP-L3 in HCC surveillance. Our work demonstrates that the GAAD (Cobas) algorithm demonstrated good clinical performance and was as sensitive and specific as the GALAD (Cobas) and GALAD (μTASWAKO) algorithms in differentiating HCC and CLD controls, across all disease stages, etiologies, and geographical regions; therefore, AFP-L3 may have a negligible role in HCC detection. Our study provides supporting evidence that in participants with CLD undergoing guideline-directed HCC surveillance, the GAAD (Cobas) algorithm may be used as an effective method for the detection of HCC, potentially resulting in improved patient outcomes.

Hepatocellular carcinoma (HCC) is often detected at advanced stages among patients with hepatitis B virus (HBV), underscoring the urgency for more precise surveillance tests. Here, we compare the clinical performance of the novel - GAAD (gender [biological sex], age, alpha-fetoprotein [AFP], protein-induced by vitamin K absence-II [PIVKA-II]) and GALAD (gender [biological sex], age, AFP, Lens-culinaris AFP [AFP-L3]), PIVKA-II) algorithms to assess the utility of AFP-L3 for distinguishing HCC from benign chronic liver disease (CLD) in Chinese patients with predominantly chronic HBV infection. Eligible adults were enrolled, and biomarkers were measured using Elecsys (Cobas) or µTASWAKO assays. In total, 411 participants provided serum samples (HCC, n = 176 [early-stage, n = 110]; CLD, n = 136; specificity n = 101). HBV was the underlying disease etiology for most participants (HCC, 95%; benign CLD, 72%). For GAAD (Cobas), GALAD (Cobas), and GALAD (µTASWAKO), AUCs were 93.1% (95% CI: 90.0–96.2), 93.2% (90.0–96.3), and 92.7% (88.4–96.9) for early-stage, and 95.6% (93.6–97.6), 95.6% (93.6–97.7), and 95.8% (93.2–98.3) for all-stage HCC, versus CLD, respectively. Interestingly, both GAAD and GALAD algorithms demonstrated comparable diagnostic performance regardless of disease etiology (HBV vs. non-HBV), presence of cirrhosis, geographic region, and within pan-tumor specificity panels (p < 0.001), indicating AFP-L3 may have a negligible role in HCC surveillance.

Cancers display dynamic interactions with their complex microenvironments that influence tumor growth, invasiveness, and immune evasion, thereby also influencing potential resistance to therapeutic treatments. The tumor microenvironment (TME) includes cells of the immune system, the extracellular matrix, blood vessels, and other cell types, such as fibroblasts or adipocytes. Various cell types forming this TME secrete exosomes, and molecules thereby released into the TME have been shown to be important mediators of cellular communication and interplay. Specific stressors in the TME, such as hypoxia, starvation, inflammation, and damage, can furthermore induce autophagy, a fundamental cellular process that degrades and recycles molecules and subcellular components, and recently it has been demonstrated that the small non-coding vault RNA1-1 plays a role as a regulator of autophagy and the coordinated lysosomal expression and regulation (CLEAR) network. Here, we demonstrate for the first time that intra-tumoral damage following effective therapeutic treatment is linked to specific intracellular synthesis and subsequent exosomal release of vault RNAs in endocrine tumors in vitro and in vivo. While we observed a subsequent upregulation of autophagic markers under classical chemotherapeutic conditions, a downregulation of autophagy could be detected under conditions strongly involving inflammatory cascades.

Background: Abdominal ultrasound is prone to hepatocellular carcinoma (HCC) surveillance failure, particularly in patients with metabolic dysfunction-associated steatotic liver disease (MASLD) or alcohol-associated liver disease (ALD), prompting growing interest in blood-based biomarkers as an alternative strategy. Methods: We conducted a case–control study evaluating two blood-based biomarker panels, GAAD and GALAD, for detection of early-stage HCC (Barcelona Clinic Liver Cancer (BCLC) stage 0 or A) in patients with MASLD or ALD cirrhosis. Blood specimens were collected within 6 months of HCC diagnosis (cases); controls were patients with cirrhosis but without HCC. GAAD and GALAD scores were measured using the Roche Elecsys platform, applying validated cutoffs of 2.57 and 2.47, respectively. Sensitivity and specificity were compared between the panels and versus ultrasound plus alpha fetoprotein (AFP) using McNemar’s chi square test. Results: Of 152 patients (56.6% men), 46.7% had HCC (54.9% BCLC 0/A) and 53.3% had cirrhosis without HCC. GAAD and GALAD each achieved a sensitivity of 87.2% for early-stage HCC, with specificities of 69.1% and 67.9%, respectively. In paired analyses (n = 90), GAAD had higher sensitivity for any-stage HCC (89.5% vs. 68.4%, p = 0.046) but lower specificity (71.8% vs. 93.0%, p = 0.006) than ultrasound plus AFP. GAAD and GALAD demonstrated consistently higher sensitivity than ultrasound plus AFP across subgroups by age, sex, cirrhosis etiology, and Child Pugh class. Conclusion: In this case–control study of patients with non-viral cirrhosis, GAAD and GALAD demonstrated high sensitivity for early-stage HCC. These findings highlight the potential of blood-based biomarkers to improve HCC surveillance in contemporary populations.