Abstract The properties of cancer-associated genetic changes in cell-free DNA (cfDNA) are not fully understood. We performed whole-genome sequencing (WGS) of cfDNA as well as tumor tissue and white blood cells (WBCs) from 1,807 samples of 1,064 patients across eight common cancer types. Characterization of single base substitutions, small insertions and deletions, structural variants (SVs), and phased variants in single cfDNA molecules revealed unique properties of tumor-derived alterations as well as differences in error rates that spanned orders of magnitude. Given the low error rate associated with detection of tumor-specific rearrangement junctions in cfDNA, we hypothesized that these types of changes could enable detection of circulating tumor DNA (ctDNA) without prior knowledge of the alterations in the tumor tissue. As an example of this approach, we scanned each sequenced fragment genome-wide in cfDNA samples from the CheckPAC trial of patients with metastatic pancreatic cancer treated with radiation and immunotherapy to identify putative rearrangement junctions. We identified 22,010,911 such fragments but only 1,572 (0.007%) and 58,339 (0.27%) of these were present in the matched tumor or WBC samples, respectively, with the remaining identified only in cfDNA. We characterized each cfDNA fragment by the SV type, SV size, microhomology and insertion at the breakpoint junction, fragment size, and the location of the breakpoint with respect to the nearest fragment end, identifying differences depending on the origin of the SV. Machine learning analyses of SVs from cfDNA resulted in a high cross-validated performance for detection of tumor-specific SVs with an area under the curve (AUC) of 0.97 (95% CI: 0.97-0.98). After enriching for fragments most likely to be tumor-derived, we found that the number of cfDNA fragments containing SVs was highly correlated with the number obtained using a tumor-informed approach (Pearson correlation coefficient = 0.87, p<0.001), and could recapitulate longitudinal ctDNA levels and clinical outcomes using only low-coverage (∼4x) plasma WGS. The universal nature of tumor-associated sequence and structural alterations in cfDNA may be broadly useful for cancer detection. Citation Format: Daniel C. Bruhm, Carolyn Hruban, Adrianna L. Bartolomucci, Akshaya V. Annapragada, Sarah Short, Shashikant Koul, Kaui P. Lebarbenchon, Julia S. Johansen, Inna M. Chen, Andrei Sorop, Razvan Iacob, Speranta Iacob, Liana Gheorghe, Simona Dima, Katherine A. McGlynn, Manuel Ramírez-Zea, John Groopman, PLCRC-MEDOCC group, Remond J. Fijneman, Gerrit A. Meijer, Zachariah H. Foda, Jillian Phallen, Robert B. Scharpf, Victor E. Velculescu. Sequence and structural DNA alterations in the circulation of patients with cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2591.

Abstract INTRODUCTION: Liver disease occurs on a continuum from steatosis to fibrosis, cirrhosis and ultimately hepatocellular carcinoma (HCC), with a 30% lifetime risk of HCC among those with cirrhosis (LCr). If identified early, steatosis and fibrosis are potentially reversible, and in LCr, surveillance can reduce cancer morbidity and mortality. Despite these benefits, conventional LCr detection modalities are invasive or have limited performance. We previously demonstrated that cost-effective liquid biopsies of genome-wide cell-free DNA (cfDNA) fragmentomes enable early detection of HCC. Here, we use these technologies to detect liver steatosis, fibrosis, and cirrhosis towards improved pre-cancer intervention and HCC surveillance. METHODS: We performed low-coverage, whole genome sequencing of plasma cfDNA from separate Discovery (n=423) and Validation (n=221) cohorts including individuals with no known liver disease (n=397), chronic liver disease and early fibrosis (n=91) including viral hepatitis and metabolic associated steatotic liver disease, or advanced fibrosis/cirrhosis (n=156). We computed genome-wide fragment length, coverage, and repeat element features (DELFI and ARTEMIS), cross-validated a machine learning classifier for fibrosis and LCr detection in the Discovery Cohort and evaluated the locked model in the Validation Cohort. We then performed whole methylome sequencing (n=28) and cell-type deconvolution to reveal mechanisms of change to cfDNA fragmentomes in LCr. RESULTS: Individuals with early liver disease/fibrosis and advanced fibrosis/cirrhosis were detected with high performance (AUC=0.90, 95% CI=0.86-0.95 and AUC=0.95, 95% CI=0.93-0.98, respectively) in the Discovery Cohort. At an 80% specificity locked cutpoint, Validation Cohort sensitivity was 70.8% (90% CI=52.3%-87.5%) for early liver disease/fibrosis and 90.1% (90% CI=84.4%-94.4%) for advanced fibrosis/cirrhosis. The model displayed low cross-reactivity for other fibrotic origin conditions including benign lung nodules or chronic pancreatitis (median scores 0.087 and 0.068 respectively vs. 0.55 for LCr, p<0.0002). The approach outperformed the existing fibrosis index FIB-4, detecting 5.07x (95% CI=3.03-17.35) and 1.2x (95% CI=1.18-1.32) more cases of early liver disease/fibrosis and advanced fibrosis/cirrhosis in simulations. cfDNA methylome deconvolution revealed increased contributions of liver endothelium (p=0.00016) and blood monocytes (p=5.2x10-5) and decreased contribution of hepatocytes (p=0.00035) with shorter fragment lengths in LCr. CONCLUSIONS: A cfDNA fragmentome biomarker enabled early detection of liver disease including LCr and reflected both liver-derived and immune-cell related changes. These analyses may enable accessible early detection of pre-cancer conditions with potential to improve liver disease management and early detection of HCC. Citation Format: Akshaya Vijaya Annapragada, Zachariah Foda, Hope Orjuela, Carter Norton, Shashi Koul, Noushin Niknafs, Sarah Short, Keerti Boyapati, Adrianna Bartolomucci, Dimitrios Mathios, Michael Noe, Chris Cherry, Jacob Carey, Alessandro Leal, Bryan Chesnick, Nic Dracopoli, Jamie Medina, Nicholas Vulpescu, Daniel Bruhm, Sarah Bacus, Vilmos Adleff, Amy Kim, Steve Baylin, Greg Kirk, Andrei Sorop, Razvan Iacob, Speranta Iacob, Liana Gheorghe, Simona Dima, Katherine McGlynn, Manuel Ramirez-Zea, Claus Feltoft, Julia Johansen, John Groopman, Jillian Phallen, Rob Scharpf, Victor Velculescu. Non-invasive early detection of cancer-predisposing liver diseases using genome-wide cfDNA fragmentomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4074.

Accessible liquid biopsies, including analyses of genome-wide cell-free DNA (cfDNA) fragmentation, are emerging for early detection of cancer but remain largely unexplored in other diseases. Here, we used whole-genome sequencing to examine cfDNA fragmentomes in 1576 individuals, including those with liver disease or with other morbidities such as vascular, autoimmune, and neurodegenerative conditions. As a prototype for disease-specific cfDNA fragmentomic biomarkers, we developed a machine learning classifier that detected early liver disease, advanced fibrosis, and cirrhosis with high sensitivity in separate discovery (n = 423) and validation cohorts (n = 221) and had limited cross-reactivity for other diseases. Genome-wide fragmentome and methylome analyses revealed liver-derived and immune-mediated changes in cfDNA in the circulation of individuals affected with liver disease. Fragmentomic changes were also observed across a range of other human morbidities and reflected disease-specific changes in the circulation. A machine learning model using cfDNA fragmentomes predicted overall survival in separate morbidity discovery (n = 571) and validation cohorts (n = 231). These analyses demonstrate the connection between cfDNA fragmentomes and an individual's physiologic state and provide previously unrecognized possibilities for cfDNA liquid biopsies across human disease.

Hepatocellular carcinoma (HCC) is a leading cause of cancer death globally with increasing mortality due to emerging metabolic risk factors. Here, we show that in 377 individuals with and without HCC from two geographic cohorts, cell-free DNA (cfDNA) fragmentome characteristics, including chromatin, genomic, methylome, mutational, and repeat element profiles, were altered in patients with cancer of different etiologies, including metabolic risk factors and aflatoxin exposure. A novel methylation-based tissue-of-origin algorithm (MethID) identified cfDNA fragmentome changes originating from liver, vascular, and immune cells in cancer patients. A locked cfDNA fragmentome classifier detected HCC across stages and etiologies, outperforming alpha-fetoprotein (AFP). Combining cfDNA fragmentomes, AFP, and clinical risk achieved high sensitivity in early- and late-stage cancers in both cohorts and was more sensitive than conventional approaches for detecting early-stage disease. This study provides insights into cfDNA origins for populations at risk and validates a genome-wide fragmentome approach for non-invasive detection of HCC.

Cholangiocarcinoma (CCA) is an aggressive, heterogeneous malignancy with limited effective treatment options. One of the key epigenetic dysregulations in CCA is aberrant DNA hypermethylation, suggesting that targeted DNA methylation is a promising therapeutic strategy for this disease. However, there is still limited information on how effective DNA demethylating agents are in the treatment of CCA in the clinical setting, and further studies are urgently needed to evaluate their potential benefits. Here, we established four patient-derived CCA cell lines and demonstrated that the DNA methyltransferase (DMNT) inhibitors decitabine and azacitidine had minimal effects on inhibiting CCA proliferation. A combinatorial drug screen identified PARP inhibitors as sensitizers that synergistically enhanced the antitumor effects of decitabine. The combination of DNMT inhibitors and PARP inhibitors therapeutically inhibited the growth of CCA cancers in multiple in vitro cancer cell lines and organoid models, as well as in vivo cell line-derived xenografts, patient-derived xenograft models, and CCA in mice induced by hydrodynamic tail vein injection. Mechanistically, transcriptomic profiling analysis showed that combination treatment activated the inflammatory signaling pathway and suppressed the cell cycle-related pathways in CCA. In addition, the combination synergistically induced DNA damage and cellular senescence of CCA cancer cells. Together, our study provides a preclinical proof-of-concept for the use of DNMT inhibitors in combination with PARP inhibitors as a novel therapeutic strategy and potentially optimizes current clinical practice in the treatment of CCA.

80% of adults in the US have metabolic risk factors for Liver Cirrhosis (LCr), but LCr diagnosis is challenging. Elastography and blood-based fibrosis indices have limited performance, and biopsies are invasive. The lifetime risk of hepatocellular carcinoma (HCC) in individuals with LCr is ∼30%, yet <20% of individuals undergo any HCC surveillance. We previously demonstrated that genome-wide cell-free DNA (cfDNA) fragmentomes can detect HCC in the blood. Here, we expand these approaches to pre-neoplasia, for LCr detection to facilitate management and HCC surveillance. We evaluated cfDNA fragmentomes in separate Discovery (n=465) and External Validation (n=279) Cohorts. These cohorts comprised individuals with LCr (n=132), at high-risk for LCr with viral hepatitis (n=26), metabolic associated steatotic liver disease (MASLD) and/or non-cirrhotic fibrosis (n=44), or aflatoxin exposure (n=10), or from healthy screening populations (n=532, including 126 with metabolic risk factors). For all individuals, we extracted cfDNA from plasma, performed low coverage (1-2x) whole genome sequencing, and computed genome-wide fragment length, coverage and repeat element features (DELFI and ARTEMIS). We cross-validated a machine learning model with these features for detection of LCr in the Discovery Cohort and evaluated the locked model in the Validation Cohort. In the Discovery Cohort, individuals with LCr were detected with high performance (AUC=0.97, 95% CI 0.94-1.0 and AUC=0.95, 95% CI=0.92-0.98, for individuals with and without metabolic risk factors). Scores were higher in LCr than in healthy populations and increased with cirrhosis severity (p<3.2x10-6 for Child-Pugh A, B and C). In the Validation Cohort, the locked model achieved 78% sensitivity and 92% specificity when locked at a threshold of 90% specificity and 90% sensitivity in the Discovery Cohort (AUC=0.95, 95% CI=0.91-0.99, and AUC=0.93, 95% CI=0.89-0.97, for individuals with and without metabolic risk factors), outperforming common fibrosis indices APRI and FIB-4. Among high-risk individuals without LCr but with aflatoxin exposure, MASLD, or fibrosis, scores were higher than in healthy individuals (p<6.0x10-16), but remained lower than for individuals with LCr (p<2.2x10-16). Fragmentomic analyses of transcription factor binding sites and single nucleotide variants revealed molecular alterations linked to both liver-tissue derived and inflammatory changes of cirrhosis. cfDNA fragmentomes enable detection of LCr, a pre-cancer condition that increases HCC risk. HCC surveillance in high-risk populations is critical, but accessibility and adherence remain low. A facile, effective screening approach for LCr may enable early identification towards improved management and initiation of HCC surveillance. Akshaya V. Annapragada, Zachariah H. Foda, Noushin Niknafs, Sarah Short, Dimitrios Mathios, Shashikant Koul, Keerti Boyapati, Adrianna Bartolomucci, Jamie E. Medina, Nicholas A. Vulpescu, Chris Cherry, Daniel C. Bruhm, Vilmos Adleff, Amy Kim, Andrei Sorop, Razvan Iacob, Speranta Iacob, Liana Gheorghe, Simona Dima, Katherine A. McGlynn, Manuel Ramirez-Zea, John Groopman, Jillian Phallen, Robert B. Scharpf, Victor E. Velculescu. Cell-free DNA fragmentomes enable early identification of liver cirrhosis to facilitate cancer surveillance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6426.

With approximately one million diagnosed cases and over 700,000 deaths recorded annually, gastric cancer (GC) is the third most common cause of cancer-related deaths worldwide. GC is a heterogeneous tumor. Thus, optimal management requires biomarkers of prognosis, treatment selection, and treatment response. The Cancer Genome Atlas program sub-classified GC into molecular subtypes, providing a framework for treatment personalization using traditional chemotherapies or biologics. We hypothesized that integrating immunohistochemistry markers, tumor gene expression profiles, and serum cytokines would define biologically distinct subtypes of gastric cancer and associate with overall survival independently of clinicopathologic factors and provide incremental prognostic value beyond existing classifications. Here, we report a comprehensive study of GC vascular and immune markers associated with tumor microenvironment (TME) based on stage and molecular subtypes, and their correlation with outcomes. Using tissues and blood circulating biomarkers and a molecular classification, we identified tumor archetypes, which show that the TME evolves with the disease stage and is a determinant of prognosis. Moreover, our TME-based subtyping strategy allowed the identification of archetype-specific prognostic biomarkers such as CDH1-mutant GC and circulating IL-6 that provided information beyond and independent of TMN staging, MSI status, and consensus molecular subtyping. The results show that integrating molecular subtyping with TME-specific biomarkers could contribute to improved patient prognostication and may provide a basis for treatment stratification, including for contemporary anti-angiogenesis and immunotherapy approaches.

Tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) is a member of the TNF protein superfamily and was initially identified as a protein capable of inducing apoptosis in cancer cells. In addition, TRAIL can promote pro-survival and proliferation signaling in various cell types. Subsequent studies have demonstrated that TRAIL plays several important roles in immunoregulation, immunosuppression, and immune effector functions. Type 1 diabetes (T1D) is an autoimmune disease characterized by hyperglycemia due to the loss of insulin-producing β-cells, primarily driven by T-cell-mediated pancreatic islet inflammation. Various genetic, epigenetic, and environmental factors, in conjunction with the immune system, contribute to the initiation, development, and progression of T1D. Recent reports have highlighted TRAIL as an important immunomodulatory molecule with protective effects on pancreatic islets. Experimental data suggest that TRAIL protects against T1D by reducing the proliferation of diabetogenic T cells and pancreatic islet inflammation and restoring normoglycemia in animal models. In this review, we aimed to summarize the consequences of TRAIL action in T1D, focusing on and discussing its signaling mechanisms, role in the immune system, and protective effects in T1D.

Background: Cholangiocarcinoma (CCA) is a fatal cancer of the bile duct with a poor prognosis owing to limited therapeutic options. The incidence of intrahepatic CCA (iCCA) is increasing worldwide, and its molecular basis is emerging. Environmental factors may contribute to regional differences in the mutation spectrum of European patients with iCCA, which are underrepresented in systematic genomic and transcriptomic studies of the disease. Methods: We describe an integrated whole-exome sequencing and transcriptomic study of 37 iCCAs patients in Germany. Results: We observed as most frequently mutated genes ARID1A (14%), IDH1, BAP1, TP53, KRAS, and ATM in 8% of patients. We identified FGFR2::BICC1 fusions in two tumours, and FGFR2::KCTD1 and TMEM106B::ROS1 as novel fusions with potential therapeutic implications in iCCA and confirmed oncogenic properties of TMEM106B::ROS1 in vitro. Using a data integration framework, we identified PBX1 as a novel central regulatory gene in iCCA. We performed extended screening by targeted sequencing of an additional 40 CCAs. In the joint analysis, IDH1 (13%), BAP1 (10%), TP53 (9%), KRAS (7%), ARID1A (7%), NF1 (5%), and ATM (5%) were the most frequently mutated genes, and we found PBX1 to show copy gain in 20% of the tumours. According to other studies, amplifications of PBX1 tend to occur in European iCCAs in contrast to liver fluke-associated Asian iCCAs. Conclusions: By analyzing an additional European cohort of iCCA patients, we found that PBX1 protein expression was a marker of poor prognosis. Overall, our findings provide insight into key molecular alterations in iCCA, reveal new targetable fusion genes, and suggest that PBX1 is a novel modulator of this disease.

Abstract Hepatocellular carcinoma (HCC) is a leading cause of cancer death world-wide. In the US, liver cancer has increased in incidence and mortality due to a growing population from South and Central America, which faces higher risk of disease in part due to aflatoxin exposure. Recently, we showed that the DELFI (DNA evaluation of fragments for early interception) approach using genome-wide cell free DNA (cfDNA) fragmentation profiles and machine learning can be used for detection of liver and other cancers. Having previously demonstrated that a DELFI classifier accurately detects HCC in populations from the US and Hong Kong, we evaluated the classifier in other clinically relevant cohorts worldwide. Here we show that approach generalizes to diverse populations, and that including other genomic and protein features from the same blood draw improves performance. We examined plasma samples from 377 individuals, including 244 individuals with HCC and 133 without cancer, including 85 with cirrhosis. Plasma samples were collected from individuals with or without HCC in a case-control study in Guatemala (n=203) and from a prospective collection in Romania (n=174) and cfDNA was analyzed by whole- genome sequencing at ∼10x coverage. The median DELFI scores using a locked classifier (Foda et al., Cancer Discovery, 2023) were higher in both cohorts for patients with cancer across all stages compared to individuals without cancer, regardless of the presence of cirrhosis. Using the locked model with a threshold that corresponded to 80% specificity in prior work, DELFI detected individuals with HCC with sensitivities of 90% and 69% in the two cohorts at specificities of 92% and 86%, respectively. For early-stage HCC within Milan Criteria for liver transplantation, sensitivities were 85% in the case-control cohort and 64% in the prospective cohort. In these cohorts, the fixed DELFI model outperformed AFP at the clinically used threshold of 20 ng/mL with a sensitivity in the combined cohorts of 78% at 91% specificity, compared to 63% sensitivity at 91% specificity for AFP. A combined approach using either DELFI at a threshold that corresponded to a 90% specificity in our previous study or AFP at the clinical threshold resulted in 82% sensitivity (74% in early stage) at 92% specificity and was superior to estimates of AFP and ultrasound for early-stage disease (63% sensitivity at 84% specificity). Individuals who tested positive with DELFI had a significantly shorter overall survival (p=0.002, log rank test), even amongst individuals at the earliest stage, while AFP alone did not stratify survival for patients with early-stage disease. Single-molecule analyses from low coverage WGS of cfDNA revealed genome-wide mutational profiles that were similar to those of HCC and in individuals from Guatemala that were characteristic of aflatoxin exposure. Overall, this work provides insight into the origins of cfDNA in populations at risk for HCC and validates our genome-wide fragmentome approach for non-invasive cancer detection that may facilitate liver cancer screening. Citation Format: Zachariah H Foda, Daniel Bruhm C Bruhm, Akshaya V Annapragada, Shashikant Koul, Sarah Short, Keerti Boyapati, Adrianna Bartolomucci, Vilmos Adleff, Nicholas A Vulpescu, Hope Orjuela, Andrei Sorop, Razvan Iacob, Liana Gheorghe, Simona Dima, Katherine A McGlynn, Manuel Ramírez-Zea, Jillian Phallen, John Groopman, Robert B Sharpf, Victor E Velculescu. Early detection of liver cancer from diverse populations using cfDNA fragmentome and protein biomarkers [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A050.

Introduction/Background Ovarian cancer remains an aggressive malignancy with poor rates in terms of survival even in cases in which debulking surgery to no residual disease is achieved. Therefore, attention was focused on identifying other prognostic markers which might be associated with poorer outcomes in order to provide a better selection of cases submitted to per primam surgery Methodology Data of patients submitted to primary debulking surgery between 2014 -2020 in Ion Cantacuzino hospital were retrospectively reviewed. Finally a total number of 107 patients was identified. Preoperative data regarding laboratory tests, intraoperative data regarding the completeness of cytoreduction and postoperative data regarding the long term outcomes were reviewed. A serum value of 136 for natrium was considered as cut off, patients being further classified in cases with hyponatremia – 41 cases and cases with normal natrium levels – 66 cases. Results Patients diagnosed with preoperative hyponatremia proved to be diagnosed more often in advanced stages of the disease (IIIC,IV) when compared to those with normal natrium values (p=0,0012). Moreover, among patients diagnosed in advanced stages (FIGO IIIC and IV) hyponatremia was more often encountered in cases in which debulking surgery was not achieved (p=0,003). Meanwhile, hyponatremia was also found to be statistically significant associated with a higher volume of ascites (p=0,002), with lower levels of serum albumin (p=0,004) and with higher rates of postoperative complications (p=0,004). As for the long term outcomes, patients diagnosed with preoperative hyponatremia and advanced stages of the disease reported a significantly poorer overall survival when compared to those with normal sodium levels. However, this difference was not statistically significant when comparing the overall survivals between hyponatremic and normonatremic patients along all stages of the disease. Conclusion Preoperative hyponatremia might become an useful tool in order to identify caseswith poorer outcomes especially among advanced stages of the disease. Disclosures None.

Introduction/Background Both nutritional and inflammatory status seem to play a central role in the evolution of ovarian cancer patients. The aim of the current paper is to investigate the association between C reactive protein to albumin ratio and the postoperative outcomes of ovarian cancer patients. Methodology In the current paper we introduced 107 patients diagnosed with epithelial ovarian cancer submitted to per primam debulking surgery. An optimal cutoff value of 0,75 was obtained using the receiver operation curve Results Higher levels of this parameter were significantly associated with higher values of CA125 (p=0,02), higher stages (p=0,04), incomplete debulking (p=0,02) and with more frequent postoperative complications (p=0,004). When it comes to the long term outcomes, higher values of CRP/albumin ratio were associated with significantly poorer disease free and overall survival (12,3 and 18 months respectively) when compared to cases with lower values of this parameter (15,1 months and 26 months respectively) (p=0,001 and p=0,0004 respectively). Conclusion CRP/albumin ratio represents a significant prognostic marker which seems to identify cases at risk to have a poorer evolution after per primamdebulking surgery. Therefore such cases might benefit more if neoadjuvant chemotherapy is administrated. Disclosures None.

OBJECTIVES:Cholangiocarcinoma (CCA) is a heterogeneous malignancy with high mortality and dismal prognosis, and an urgent clinical need for new therapies. Knowledge of the CCA epigenome is largely limited to aberrant DNA methylation. Dysregulation of enhancer activities has been identified to affect carcinogenesis and leveraged for new therapies but is uninvestigated in CCA. Our aim is to identify potential therapeutic targets in different subtypes of CCA through enhancer profiling. DESIGN:Integrative multiomics enhancer activity profiling of diverse CCA was performed. A panel of diverse CCA cell lines, patient-derived and cell line-derived xenografts were used to study identified enriched pathways and vulnerabilities. NanoString, multiplex immunohistochemistry staining and single-cell spatial transcriptomics were used to explore the immunogenicity of diverse CCA. RESULTS:We identified three distinct groups, associated with different etiologies and unique pathways. Drug inhibitors of identified pathways reduced tumour growth in in vitro and in vivo models. The first group (ESTRO), with mostly fluke-positive CCAs, displayed activation in estrogen signalling and were sensitive to MTOR inhibitors. Another group (OXPHO), with mostly BAP1 and IDH-mutant CCAs, displayed activated oxidative phosphorylation pathways, and were sensitive to oxidative phosphorylation inhibitors. Immune-related pathways were activated in the final group (IMMUN), made up of an immunogenic CCA subtype and CCA with aristolochic acid (AA) mutational signatures. Intratumour differences in AA mutation load were correlated to intratumour variation of different immune cell populations. CONCLUSION:Our study elucidates the mechanisms underlying enhancer dysregulation and deepens understanding of different tumourigenesis processes in distinct CCA subtypes, with potential significant therapeutics and clinical benefits.

Introduction/Background Anemia represents a common finding among neoplastic patients and is caused by multiple mechanisms including due to the inflammatory status induced by the presence of malignant cells. The aim of the current paper is to investigate the correlation between these two entities among cases diagnosed with advanced stage ovarian ca Methodology Preoperative data of patients submitted to debulking surgery between 2014–2020 in Ion Cantacuzino hospital were retrospectively reviewed. Results A total number of 57 patients were considered as eligible for this study: By using the receiver operation curve (ROC) a cut off value of 841000 was obtained with an area under the ROC curve (AUC) of 0,787 (sensibility=0,83, 1- specificity=0,29). According to this value the study group was divided in two subgroups: the first one included patients with SII < 841.000 – 20 cases while the second one included patients with SII >841.000 - 37 cases. When it comes to the preoperative level of hemoglobin, a mean value of 12,2 g/dl was obtained, this value being significantly lower among patients with higher levels of SII (11,4g/dl) versus those with lower SII levels (and in which the mean preoperative value of hemoglobin was of 13,1 g/dl) (p=0,005). Moreover, when analyzing the preoperative data, there were 41 cases in FIGO stage IIIC and respectively 16 cases diagnosed in FIGO stage IV. Patients diagnosed with FIGO stage IIIC of disease had a mean value of SII of 789001 while cases diagnosed in FIGO stage IV of disease had a mean SII value of 1890256 (p=0,003) and respectively a mean value of hemoglobin of 12,8 g/dl versus 10,8 g/dl (p=0,002). Conclusion Preoperative levels of hemoglobin seem to be significantly correlated with preoperative SII values; meanwhile both values seem to be significantly corelated with FIGO stage in advanced stage ovarian cancer. Disclosures None.

Introduction/Background The extent of peritoneal carcinomatosis represents the most frequently encountered reason for incomplete debulking in advanced stage ovarian cancer. Therefore, attention was focused on identifying a prognostic marker which might provide a better identification of these cases preoperatively. Systemic inflammatory index, defined as the platelets*neutrophils/lymphocytes seems to provide significant information regarding the extent of the disease. Methodology Between 2014–2020 57 patients diagnosed with peritoneal carcinomatosis from ovarian cancer were submitted to surgery in Ion Cantacuzino hospital. Patients were further classified in three groups according to the extent of peritoneal carcinomatosis (defined by the peritoneal carcinomatosis index – PCI): PCI<10 – 14 cases, PCI between 10–15 – 21 cases and PCI>15 - 12 cases. Results Preoperative values of SII ranged between 871674 and 7458168, with a mean value of 2424479. Meanwhile, we determined the intraoperative volume of ascites, a mean value of 2350 ml being obtained (range 300–8000ml). Cases in the first group reported a mean SII level of 761786, those in the second group reported a mean SII level of 1276485 while those in the third group reported a mean SII level of 68760393 (p<0,0001). Meanwhile a positive correlation was established between the ascites volume and the preoperative level of SII (p=0,001). When analyzing the completeness of cytoreduction, maximal debulking was achieved in 46 out of the 57 cases; cases in which maximal debulking was feasible had a mean value of SII of 1175802 while cases in which debulking was incomplete had a preoperative value of SII of 4190031 (p<0,0001). Conclusion Preoperative SII seems to have a prognostic value in order to identify cases in which maximal debulking surgery is not feasible; therefore, such cases should be rather submitted to neoadjuvant chemotherapy followed by interval debulking surgery than to per primam attempt of debulking. Disclosures None.