Citations

Abstract Background: Early detection is the most potent strategy to improve survival in PDA, but its success hinges on an unresolved question: does radiologically invisible disease represent biologically early or indolent disease, or established malignancy beneath the threshold of detection? We leveraged prediagnostic CTs—incidental scans obtained 3-36 months prior to diagnosis without a focal mass—to define the relationship between imaging phenotype and tumor biology. Methods: From a multi-institutional pool of 5,046 biopsy-confirmed PDAs, we assembled a cohort of 346 prediagnostic CTs, which were independently evaluated by three radiologists using a standardized protocol. Based on majority vote, CTs were dichotomized into imaging-occult (IO) (normal pancreas) and imaging-apparent (IA) (abnormal pancreas with indirect signs such as focal atrophy, duct dilatation, etc.) groups. Tumor size and metastases (M) at diagnosis, and overall survival (OS) were compared using multivariable linear (size), logistic (M1), and Cox proportional hazards (OS) models, adjusting for lead time to diagnosis, age, sex, diabetes, CA 19-9, and surgical resection status, to isolate the independent biological relevance of the imaging phenotype. Results: IO phenotype was seen in 150 patients (mean age 66.7±11.2; 37.3% females) while 196 had IA phenotype (mean age 69.9±10.6; 49.5% females). Median lead time was 396 days (range: 90-1088) with the IA group being enriched in 3-12-month lead time (57.7% vs 33.3%; p<0.001). Both groups had comparable diabetes rates (IA 33.2% vs IO 32.7%; p=1.0), median CA 19-9 (IA 193 vs IO 322 U/mL; p=0.41), and surgical resection (IA 38.3% vs IO 38.0%; p = 1.0). While unadjusted mean tumor size at diagnosis was larger in IA group (3.8 cm vs 3.2 cm), there was no difference after adjusting for clinical factors (-7.1% difference; 95% CI: -17.2, 4.2; p=0.21). Metastases were also comparable (M rate: IA 22.4% vs IO 27.3%; adjusted OR 0.97; 95% CI: 0.50, 1.88; p=0.93). Adjusted Cox models demonstrated equivalent OS (median: 18.7 vs 17.6 months; HR 1.06; p=0.66), which persisted even when stratified by surgical status (HR 1.07; 95% CI: 0.83, 1.38; p=0.61). Even in the critical 3-12 months lead time (n=163), OS remained equivalent (HR 0.89; p=0.62), and groups did not differ in either tumor size (-6.4%; 95% CI: -22.4, 12.9; p=0.49) or metastases (OR 0.48; 95% CI 0.14, 1.59; p=0.23). Conclusions: A normal-appearing pancreas on prediagnostic imaging is common yet signifies neither early nor indolent disease—it harbors PDA biologically equivalent to the imaging-apparent pancreatic phenotype. Because the disease at this stage lies beyond human perceptual capacity, AI augmentation represents the only potential path to realizing the survival benefit of early detection. Citation Format: Khurram Khaliq Bhinder, Sovanlal Mukherjee, Armin Zarrintan, Angela Ammirabile, Ahmed Khan Jadoon, Ziding Feng, Suresh T. Chari, Ajit H. Goenka. Dissociation between prediagnostic imaging phenotype and tumor biology defines the early detection challenge in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(8_Suppl):Abstract nr LB205.

Background: Blood-based biomarker panels, including GALAD, have been proposed as an alternative to abdominal ultrasound for hepatocellular carcinoma (HCC) surveillance. Studies suggest longitudinal evaluation of biomarkers can improve test performance; however, no large studies have validated these findings. Methods: We leveraged the HCC Early Detection Strategy (HEDS) study (n=1019 patients with cirrhosis; 99 incident HCC) and Texas HCC Consortium (THCCC) (n=2345 patients with cirrhosis; 126 incident HCC) to compare the performance of fixed-threshold GALAD (cutoff of −1.36), and 4 longitudinal algorithms: longitudinal GALAD, PALAD, mFB-ALAD, and mPEB-ALAD. The HEDS cohort was used to derive longitudinal algorithms, and external validation was performed in THCCC. Patient-level sensitivity and test-level false-positive rate (FPR) were examined overall and across subgroups by age, sex, and cirrhosis etiology. Results: In THCCC, fixed-threshold GALAD had higher sensitivity in the 6 months before HCC diagnosis (71.4%, 95% CI: 62.9%–81.7%) than longitudinal GALAD (55.1%, 95% CI: 49.3–66.4), PALAD (55.1%, 95% CI: 50.0%–70.5%), mPEB-ALAD (53.1%, 95% CI: 43.6%–62.0%), and mFB-ALAD (42.9%, 95% CI: 32.3–48.5). However, fixed-threshold GALAD had a higher FPR (25.4%, 95% CI: 23.7%–26.9%) compared with longitudinal GALAD (15.0%, 95% CI: 12.8%–15.8%), PALAD (13.0%, 95% CI: 10.2%–14.6%), and mFB-ALAD (11.2%, 95% CI: 9.6%–12.1%) but comparable to mPEB-ALAD (22.9%, 95% CI: 21.2%–23.8%). In subgroup analyses, fixed-threshold GALAD had the highest FPR in males (35.6%) and those aged ≥65 (43.5%); longitudinal algorithms had significantly lower FPRs in subgroups but with lower sensitivity for HCC. Conclusions: Improvements in FPRs with longitudinal GALAD algorithms, as compared with fixed-threshold GALAD, are offset by significantly decreased sensitivity for HCC detection.

AbstractBackgroundMolecular studies have tried to address the unmet need for prognostic biomarkers in prostate cancer (PCa). Some gene expression tests improve upon clinical factors for prediction of outcomes, but additional tools for accurate prediction of tumor aggressiveness are needed.MethodsBased on a previously published panel of 23 gene transcripts that distinguished patients with metastatic progression, we constructed a prediction model using independent training and testing datasets. Using the validated messenger RNAs and Gleason score (GS), we performed model selection in the training set to define a final locked model to classify patients who developed metastatic‐lethal events from those who remained recurrence‐free. In an independent testing dataset, we compared our locked model to established clinical prognostic factors and utilized Kaplan‐Meier curves and receiver operating characteristic analyses to evaluate the model's performance.ResultsThirteen of 23 previously identified gene transcripts that stratified patients with aggressive PCa were validated in the training dataset. These biomarkers plus GS were used to develop a four‐gene (CST2, FBLN1, TNFRSF19, and ZNF704) transcript (4GT) score that was significantly higher in patients who progressed to metastatic‐lethal events compared to those without recurrence in the testing dataset (P = 5.7 × 10−11). The 4GT score provided higher prediction accuracy (area under the ROC curve [AUC] = 0.76; 95% confidence interval [CI] = 0.69‐0.83; partial area under the ROC curve [pAUC] = 0.008) than GS alone (AUC = 0.63; 95% CI = 0.56‐0.70; pAUC = 0.002), and it improved risk stratification in subgroups defined by a combination of clinicopathological features (ie, Cancer of the Prostate Risk Assessment‐Surgery).ConclusionOur validated 4GT score has prognostic value for metastatic‐lethal progression in men treated for localized PCa and warrants further evaluation for its clinical utility.

Abstract Background: The GALAD score is a serum biomarker–based model that predicts the probability of having hepatocellular carcinoma (HCC) in patients with chronic liver disease. We aimed to assess the performance of the GALAD score in comparison with liver ultrasound for detection of HCC. Methods: A single-center cohort of 111 HCC patients and 180 controls with cirrhosis or chronic hepatitis B and a multicenter cohort of 233 early HCC and 412 cirrhosis patients from the Early Detection Research Network (EDRN) phase II HCC Study were analyzed. Results: The area under the ROC curve (AUC) of the GALAD score for HCC detection was 0.95 [95% confidence interval (CI), 0.93–97], which was higher than the AUC of ultrasound (0.82, P <0.01). At a cutoff of −0.76, the GALAD score had a sensitivity of 91% and a specificity of 85% for HCC detection. The AUC of the GALAD score for early-stage HCC detection remained high at 0.92 (95% CI, 0.88–0.96; cutoff −1.18, sensitivity 92%, specificity 79%). The AUC of the GALAD score for HCC detection was 0.88 (95% CI, 0.85–0.91) in the EDRN cohort. The combination of GALAD and ultrasound (GALADUS score) further improved the performance of the GALAD score in the single-center cohort, achieving an AUC of 0.98 (95% CI, 0.96–0.99; cutoff −0.18, sensitivity 95%, specificity 91%). Conclusions: The performance of the GALAD score was superior to ultrasound for HCC detection. The GALADUS score further enhanced the performance of the GALAD score. Impact: The GALAD score was validated in the United States.

Abstract High-quality and well-annotated biorepositories are needed to better understand the pathophysiology and biologic mechanisms of chronic pancreatitis (CP) and its consequences. We report a methodology for the development of a robust standard operating procedure (SOP) for a biorepository based on the experience of the clinical centers within the consortium to study Chronic Pancreatitis, Diabetes and Pancreas Cancer Clinical Centers (CPDPC), supported by the National Cancer Institute and the National Institute for Diabetes and Digestive and Kidney Diseases as a unique multidisciplinary model to study CP, diabetes, and pancreatic cancer in both children and adults. Standard operating procedures from the CPDPC centers were evaluated and consolidated. The literature was reviewed for standard biorepository operating procedures that facilitated downstream molecular analysis. The existing literature on biobanking practices was harmonized with the SOPs from the clinical centers to produce a biorepository for pancreatic research. This article reports the methods and basic principles behind the creation of SOPs to develop a biorepository for the CPDPC. These will serve as a guide for investigators developing biorepositories in pancreas research. Rigorous and meticulous adherence to standardized biospecimen collection will facilitate investigations to better understand the pathophysiology and biologic mechanisms of CP, diabetes, and pancreatic cancer.

Abstract Prospective Evaluation of Chronic Pancreatitis for Epidemiologic and Translational Studies (PROCEED) is the first prospective, observational cohort study of chronic pancreatitis (CP) in the United States. The primary goals of PROCEED are to define disease progression, test the predictive capability of candidate biomarkers, and develop a platform to conduct translational and mechanistic studies in CP. Using objective and consensus-driven criteria, PROCEED will enroll adults at different stages of CP—controls, suspected CP, and definite CP. In addition to collecting detailed information using structured case report forms and protocol-mandated evaluations at baseline and during follow-up, PROCEED will establish a linked biorepository of blood, urine, saliva, stool, pancreatic fluid, and pancreatic tissue. Enrollment for PROCEED began in June 2017. As of July 1, 2018, nine clinical centers of the Consortium for the Study of Chronic Pancreatitis, Diabetes, and Pancreatic Cancer are enrolling, and 350 subjects have completed baseline evaluation. In conclusion, PROCEED will provide the most accurate and reliable estimates to date on progression of CP. The established cohort and biorepository will facilitate numerous analyses, leading to new strategies for diagnosis, methods to monitor disease progression, and treatment of CP.

Abstract The National Cancer Institute and the National Institute for Diabetes and Digestive and Kidney Diseases initiated the Consortium for the Study of Chronic Pancreatitis, Diabetes, and Pancreatic Cancer (CPDPC) in 2015 (the CPDPC's origin, structure, governance, and research objectives are described in another article in this journal). One of the key objectives of CPDPC is to assemble a cohort of 10,000 subjects 50 years or older with new-onset diabetes, called the NOD cohort. Using a define, enrich, and find early detection approach, the aims of the NOD study are to ( a ) estimate the 3-year probability of pancreatic ductal adenocarcinoma (PDAC) in NOD ( define ), (b) establish a biobank of clinically annotated biospecimens from presymptomatic PDAC and control new-onset type 2 diabetes mellitus subjects, (c) conduct phase 3 validation studies of promising biomarkers for identification of incident PDAC in NOD patients ( enrich ), and (d) provide a platform for development of a future interventional screening protocol for early detection of PDAC in patients with NOD that incorporates imaging studies and/or clinical algorithms ( find ). It is expected that 85 to 100 incidences of PDAC will be diagnosed during the study period in this cohort of 10,000 patients.

Abstract Background: The utility of alpha-fetoprotein (AFP) for hepatocellular carcinoma (HCC) surveillance is controversial. We aimed to identify factors associated with elevated AFP and define the patients for whom AFP is effective for surveillance. Methods: Data from the NCI Early Detection Research Network phase II HCC biomarker study (233 early-stage HCC and 412 cirrhotic patients) were analyzed. We analyzed 110 early-stage HCC and 362 cirrhotic hepatitis C virus (HCV) patients for external validation. Sensitivity, specificity, and area under the ROC curve (AUC) for HCC were calculated. Results: HCV etiology, non-White race, and serum alanine transaminase (ALT) predicted elevated AFP in cirrhotics. Non-White race and ALT predicted elevated AFP in HCC patients. Higher AUC of AFP for HCC was noted in patients with HBV (0.85) and alcohol (0.84), whereas it was lower in patients with hepatitis C virus (HCV; 0.80) and nonviral/alcohol etiology (0.76). The AUC was higher in HCV patients with serum ALT ≤40 U/L than patients with serum ALT >40 U/L (0.91 vs. 0.75, P < 0.01). At 90% specificity, the sensitivity of AFP increased from 44% to 74% in Whites with HCV and from 50% to 85% in non-Whites with HCV. There was a trend toward higher AUC in HCV patients with serum ALT ≤40 U/L than those with serum ALT >40 U/L (0.79 vs. 0.69, P = 0.10) in the validation cohort. Conclusions: The satisfactory performance of AFP in HCV patients with normal ALT should be further validated. Impact: The AFP may serve as a valuable surveillance test in HCV patients with normal ALT. Cancer Epidemiol Biomarkers Prev; 26(7); 1085–92. ©2017 AACR.

Abstract Inflammation plays a role in the progression to cancer and it is linked to the presence of senescent cells. Ulcerative colitis (UC) is a chronic inflammatory disease that predisposes to colorectal cancer. Tumorigenesis in this setting is associated with telomere shortening that can be observed in the nondysplastic epithelium of UC patients with high-grade dysplasia (HGD) or cancer (UC progressors). We hypothesized that a preneoplastic field of inflammation, telomere shortening, and senescence underlies tumor progression in UC progressors. Multiple biopsies of varying histologic grade were collected along the colon of nine UC progressors and analyzed for telomere length, DNA damage, senescence, p53, p16, and chronic and acute inflammation. Twenty biopsies from four UC nonprogressors and twenty-one biopsies from control individuals without UC were also analyzed. Short telomeres and increased DNA damage, senescence, and infiltrating leukocytes were observed in biopsies located less than 10 cm from HGD or cancer. Low-grade dysplasia (LGD) had the shortest telomeres along with the highest levels of senescence and infiltrating leukocytes, whereas HGD biopsies showed the opposite pattern. The expression of p16 and p53 was low in nondysplastic biopsies but progressively increased in LGD and HGD. In addition, high levels of infiltrating leukocytes were associated with telomere shortening, senescence, and reduced p53 expression. These results suggest that dysplasia arises in a preneoplastic field of chronic inflammation, which leads to telomere shortening, DNA damage, and senescence. Our findings argue that senescence acts as a tumor suppressor mechanism that is abrogated during the transition from LGD to HGD in UC. Cancer Res; 71(5); 1669–79. ©2011 AACR.