Advances In Oncology Research Articles

Enhancing the National Cancer Database content using natural language processing and electronic health record data

BackgroundThe prevalence of missing data in the National Cancer Database (NCDB) has marked implications on clinical care and research. The objective of this study was to enhance the NCDB by decreasing rates of missingness and adding new variables using automated statistical methodology. MethodsOne health system’s NCDB data from 2011–2021 was linked to electronic health record (EHR). Variables with frequent missingness and new clinically significant variables not yet included in the NCDB including patient Eastern Cooperative Oncology Group (ECOG) score, specific chemotherapy regimen, American Society of Anesthesiologists Physical Status Classification (ASA class), and discrete surgical procedure were identified in structured and unstructured EHR data. After automated incorporation of structured data from EHR, a natural language processing tool incorporating rule-based algorithms was designed to further extract variables from unstructured notes. Rates of missingness were compared between the original NCDB and the enhanced dataset, and example multivariable models were run to assess for altered model performance with reduced missingness and the addition of new clinically significant variables (chemotherapy regimen). ResultsA total of 6050 patients with NCDB records were linked to their EHR data. Prior to enhancement, rates of missingness for key variables ranged from 2.0% to 5.3%. Following dataset enhancement, missingness was significantly reduced, with relative missingness being reduced between 31.9% to 68.0%. Of the new variables added, 1367 (22.6%) of 6050 patients gained ECOG score, and 1099 (57.8%) of 1901 who received chemotherapy gained their chemotherapy regimen. Of 2989 who underwent surgery, 979 (32.8%) gained their procedure name and 621 (20.8%) gained ASA class. Comparison of the multivariable models demonstrated significant differences between the original NCDB and the enhanced dataset. Specifically, when replacing the binary predictor for chemotherapy in the original NCDB data with discrete regimens, the effect of ethnicity diminished, and the effect of radiation became significant. DiscussionWe applied statistical methodology to reduce rates of missingness in existing variables and add new variables to enrich the NCDB. While further refinement is needed to decrease missingness in new variables, this automated methodology can replace or augment manual chart review and improve the ability of to use the NCDB to study unanswered questions leading to clinical advancements in oncology.

Liquid profiling for patients with advanced cancer is ready for clinical integration

SummaryMolecular profiling of circulating tumor DNA (ctDNA) to guide treatment decisions has found its way into routine management of patients with advanced cancer. This represents a pivotal advancement in precision oncology, offering a non-invasive and fast-tracked method to detecting clinically relevant biomarkers. With the backing of international oncology guidelines, ctDNA analysis is now a standard approach to consider in molecular diagnostics. Despite the promise of ctDNA in refining treatment strategies through the detection of genomic alterations and treatment-relevant biomarkers with high concordance to tissue biopsies, challenges persist. These include the interpretation of discordances due to tumor heterogeneity, sampling biases, and technical limitations, alongside the differentiation of tumor-derived mutations from clonal hematopoiesis. The current consensus supports the utility of comprehensive genomic profiling (CGP) panels for a broad spectrum of actionable targets, while acknowledging the limitations and advocating for a balanced application of “tissue-first” and “plasma-first” approaches tailored to individual patient scenarios. The essential role of molecular tumor boards (MTBs) is in navigating the complexities of ctDNA data interpretation, thereby ensuring the effective incorporation of liquid biopsy into personalized cancer treatment regimens.

Advancements in precision oncology: Investigating the function of circulating DNA in the advancement of liquid biopsy technologies

While the traditional method is a biopsy of the potential tumor tissue, more non-invasive methods have been developed such as the liquid biopsy. It is an emerging, powerful cancer detection method that is used for molecular profiling of tumours apart from tissue-specific biopsy. It involves the analysis of free, circulating tumor genetic material and circulating tumor cells (CTCs) that are found in the fluids of the patient. This analysis helps to detect the abnormal genetic anomalies associated with the various forms of cancer as well as identify mutations corresponding to specific tumours. It is an upcoming method of diagnostics applied in the field of precision oncology that helps overcome the limitations of the traditional biopsy. It can interrogate and look through difficult-to-biopsy tumours and also aid in early cancer detection. Sequencing techniques help in building databases with different information on mutations in the genetic as well as epigenetic levels. In this review, we understand the role of liquid biopsy as not only a diagnostic tool but its role in therapeutics and its potential in the future.

Intersecting Paths: Unraveling the Complex Journey of Cancer to Bone Metastasis.

The phenomenon of bone metastases presents a significant challenge within the context of advanced cancer treatments, particularly pertaining to breast, prostate, and lung cancers. These metastatic occurrences stem from the dissemination of cancerous cells into the bone, thereby interrupting the equilibrium between osteoblasts and osteoclasts. Such disruption results in skeletal complications, adversely affecting patient morbidity and quality of life. This review discusses the intricate interplay between cancer cells and the bone microenvironment, positing the bone not merely as a passive recipient of metastatic cells but as an active contributor to cancer progression through its distinctive biochemical and cellular makeup. A thorough examination of bone structure and the dynamics of bone remodeling is undertaken, elucidating how metastatic cancer cells exploit these processes. This review explores the genetic and molecular pathways that underpin the onset and development of bone metastases. Particular emphasis is placed on the roles of cytokines and growth factors in facilitating osteoclastogenesis and influencing osteoblast activity. Additionally, this paper offers a meticulous critique of current diagnostic methodologies, ranging from conventional radiography to advanced molecular imaging techniques, and discusses the implications of a nuanced understanding of bone metastasis biology for therapeutic intervention. This includes the development of targeted therapies and strategies for managing bone pain and other skeletal-related events. Moreover, this review underscores the imperative of ongoing research efforts aimed at identifying novel therapeutic targets and refining management approaches for bone metastases. It advocates for a multidisciplinary strategy that integrates advancements in medical oncology and radiology with insights derived from molecular biology and genetics, to enhance prognostic outcomes and the quality of life for patients afflicted by this debilitating condition. In summary, bone metastases constitute a complex issue that demands a comprehensive and informed approach to treatment. This article contributes to the ongoing discourse by consolidating existing knowledge and identifying avenues for future investigation, with the overarching objective of ameliorating patient care in the domain of oncology.

Phytochemical Modulation of Ion Channels in Oncologic Symptomatology and Treatment.

Modern chemotherapies offer a broad approach to cancer treatment but eliminate both cancer and non-cancer cells indiscriminately and, thus, are associated with a host of side effects. Advances in precision oncology have brought about new targeted therapeutics, albeit mostly limited to a subset of patients with an actionable mutation. They too come with side effects and, ultimately, 'self-resistance' to the treatment. There is recent interest in the modulation of ion channels, transmembrane proteins that regulate the flow of electrically charged molecules in and out of cells, as an approach to aid treatment of cancer. Phytochemicals have been shown to act on ion channels with high specificity regardless of the tumor's genetic profile. This paper explores the use of phytochemicals in cancer symptom management and treatment.

Abstract PO4-15-05: Genomic characterization and molecular predictive biomarkers for chemotherapy in a real-world population with metastatic triple-negative breast cancer

Abstract Background: The genomic landscape of metastatic triple-negative breast cancer (mTNBC) in a real-world population is poorly defined and despite recent advances in precision oncology, molecular biomarkers for chemotherapy are largely lacking. The presence of specific genomic alterations and alterations in oncogenic pathways have the potential to provide prognostic as well as predictive information for chemotherapy, which remains the backbone treatment strategy for mTNBC. Methods: We conducted next-generation sequencing (NGS) with the FoundationOne CDx panel on tissue from the primary tumor and/or metastasis of 112 consecutive patients with mTNBC that were treated between 1998 and 2019 at 4 different Swedish hospitals. Every genomic alteration was, if applicable, subdivided into 1 of 10 canonical oncogenic pathways and noted for its involvement in the homologous recombination pathway (HRP). Frequently altered genes and pathways were then correlated with overall survival (OS) and evaluated regarding their association with progression-free survival (PFS) and response rate (RR) in patients treated with different chemotherapy agents. Tumor samples of patients with rapid progression or exceptional response to chemotherapy underwent exploratory comparison with regards to frequently altered genes and pathways and known clinical prognostic factors were compared between the two patient groups. Results: After excluding 15 patients due to insufficient quantity/quality of tumor tissue or absence of clinical data, 97 patients were analyzed. The median age at diagnosis of metastatic disease was 61 (range: 28-90), 80 % had visceral disease and 26 % received platinum-based chemotherapy in the first line setting. The most frequently altered genes were: TP53 (82 %), RAD21 (25 %), PIK3CA (23 %), MYC (22 %) and BRCA 1 or 2 (16 %). The most frequently altered pathways were TP53 (86 %), PI3K (60 %), RTK/RAS (47 %) and cell cycle (36 %). In total, 26 % of patients had an alteration in the HRP. None of the most frequently occurring genomic alterations were associated with OS. Variants of clinical significance in the HRP and BRCA1/BRCA2 genes were associated with a longer PFS in patients treated with platinum-based chemotherapy in the first line setting (HR 0.12-0.84 and 0.12-0.92). Exceptional responders to chemotherapy exhibited a more favorable clinical profile than rapid progressors (median age 51.5 vs 66.5, median Charlson comorbidity index 0.5 vs 3) whereas some numerical difference in the genomic profiling in terms of genomic alterations in MYC and RAS/RTK pathways (more often in exceptional responders) could be observed. Conclusions: We found no genomic alteration with prognostic significance in a cohort of mTNBC patients treated with chemotherapy in a real-world setting. Somatic variants of clinical significance in BRCA 1 and 2 and other HRP-related genes seem to define subgroups of patients with mTNBC that respond favorably to platinum-based chemotherapy. Further research into the genomic landscape of tumors from patients with rapid progression or exceptional response to specific treatment strategies can provide insights into mechanisms of resistance and identify new predictive biomarkers. Citation Format: Erik Olsson, Henrik Lindman, Evangelos Digkas, Viktoria Thurfjell, Haidar Mir Ali, Ute Krüger, Anna-Karin Wennstig, Marie Sundqvist, Antonis Valachis. Genomic characterization and molecular predictive biomarkers for chemotherapy in a real-world population with metastatic triple-negative breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-15-05.

Advancements in Oncology: Evolving Standards of Care and Personalized Treatment in Lung Cancer

Lung cancer remains a significant global health concern, impacting patients and healthcare systems alike. In recent years, substantial progress has been made in understanding the biology, diagnosis, and treatment of both small-cell and non-small-cell lung cancer (SCLC and NSCLC). This research paper synthesizes and reviews key findings from multiple studies published between 2007 and 2023, addressing various aspects of lung cancer researchThe studies covered in this review encompass a broad spectrum of topics, including systemic therapy, targeted treatments, genetic mutations, healthcare strategies, and patient outcomes. Notable highlights include the impact of EGFR tyrosine kinase inhibitors on NSCLC treatment, the role of nuclear factor erythroid 2-related factor 2 (NRF2) in lung adenocarcinoma, the utilization of large databases in radiation oncology research, and the importance of empathy in patient care.The paper also examines the latest developments in the molecular epidemiology of lung cancer, differences in lung cancer susceptibility among ethnic populations, and the implementation of multidisciplinary clinics for timely lung cancer care. It further delves into the significance of liquid biopsy in identifying genetic mutations for targeted therapies, the effect of ALK-positive cell percentage on the outcomes of Alectinib treatment, and the role of epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors in adjuvant therapy.Furthermore, this review assesses the impact of platinum-based chemotherapy on the survival of NSCLC patients and explores predictive factors, such as the VeriStrat test, in second-line therapy. The research also addresses the challenges and opportunities in the use of immune checkpoint inhibitors in advanced NSCLC, as well as the clinical utility of epidermal growth factor receptor (EGFR) testing in first-line therapy.In conclusion, this comprehensive review sheds light on the current state of lung cancer research, highlighting breakthroughs, challenges, and the potential for future advancements in the diagnosis and treatment of this life-threatening disease. The insights gathered from these diverse studies provide a valuable resource for clinicians, researchers, and healthcare providers in their efforts to combat lung cancer and improve patient outcomes.

Unravelling driver genes as potential therapeutic targets in ovarian cancer via integrated bioinformatics approach

Target-driven cancer therapy is a notable advancement in precision oncology that has been accompanied by substantial medical accomplishments. Ovarian cancer is a highly frequent neoplasm in women and exhibits significant genomic and clinical heterogeneity. In a previous publication, we presented an extensive bioinformatics study aimed at identifying specific biomarkers associated with ovarian cancer. The findings of the network analysis indicate the presence of a cluster of nine dysregulated hub genes that exhibited significance in the underlying biological processes and contributed to the initiation of ovarian cancer. Here in this research article, we are proceeding our previous research by taking all hub genes into consideration for further analysis. GEPIA2 was used to identify patterns in the expression of critical genes. The KM plotter analysis indicated that the out of all genes 5 genes are statistically significant. The cBioPortal platform was further used to investigate the frequency of genetic mutations across the board and how they affected the survival of the patients. Maximum mutation was reported by ELAVL2. In order to discover viable therapeutic candidates after competitive inhibition of ELAVL2 with small molecular drug complex, high throughput screening and docking studies were used. Five compounds were identified. Overall, our results suggest that the ELAV-like protein 2-ZINC03830554 complex was relatively stable during the molecular dynamic simulation. The five compounds that have been found can also be further examined as potential therapeutic possibilities. The combined findings suggest that ELAVL2, together with their genetic changes, can be investigated in therapeutic interventions for precision oncology, leveraging early diagnostics and target-driven therapy.

Predictive and Prognostic Biomarkers and Tumor Antigens for Targeted Therapy in Urothelial Carcinoma.

Urothelial carcinoma (UC) is the fourth most prevalent cancer amongst males worldwide. While patients with non-muscle-invasive disease have a favorable prognosis, 25% of UC patients present with locally advanced disease which is associated with a 10-15% 5-year survival rate and poor overall prognosis. Muscle-invasive bladder cancer (MIBC) is associated with about 50% 5 year survival when treated by radical cystectomy or trimodality therapy; stage IV disease is associated with 10-15% 5 year survival. Current therapeutic modalities for MIBC include neoadjuvant chemotherapy, surgery and/or chemoradiation, although patients with relapsed or refractory disease have a poor prognosis. However, the rapid success of immuno-oncology in various hematologic and solid malignancies offers new targets with tremendous therapeutic potential in UC. Historically, there were no predictive biomarkers to guide the clinical management and treatment of UC, and biomarker development was an unmet need. However, recent and ongoing clinical trials have identified several promising tumor biomarkers that have the potential to serve as predictive or prognostic tools in UC. This review provides a comprehensive summary of emerging biomarkers and molecular tumor targets including programmed death ligand 1 (PD-L1), epidermal growth factor receptor (EGFR), human epidermal growth factor receptor 2 (HER2), fibroblast growth factor receptor (FGFR), DNA damage response and repair (DDR) mutations, poly (ADP-ribose) polymerase (PARP) expression and circulating tumor DNA (ctDNA), as well as their clinical utility in UC. We also evaluate recent advancements in precision oncology in UC, while illustrating limiting factors and challenges related to the clinical application of these biomarkers in clinical practice.

Burden of Childhood Cancer and the Social and Economic Challenges in Adulthood

Significant advancements in pediatric oncology have led to a continuously growing population of survivors. Although extensive research is being conducted on the short-, medium-, and long-term somatic effects, reports on psychosocial reintegration are often conflicting; therefore, there is an urgent need to synthesize the evidence to obtain the clearest understanding and the most comprehensive answer. To provide a comprehensive review and analysis of the socioeconomic attainment of childhood cancer survivors (CCSs) compared with their unaffected peers. A systematic review and meta-analysis was conducted using data obtained from a comprehensive search of MEDLINE (via PubMed), Embase, and CENTRAL (Cochrane Central Register of Controlled Trials) databases on October 23, 2021; the search was updated until July 31, 2023. Eligible articles reported on educational attainment, employment, family formation, quality of life (QoL), or health-risk behavior-related outcomes of CCSs, and compared them with their unaffected peers. Study selection was performed in duplicate by 4 blinded independent coauthors. Data extraction was performed in duplicate by 4 independent authors following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Outcome measures were odds ratios (ORs) and mean differences with 95% CIs; data were pooled using a random-effects model. The search identified 43 913 articles, 280 of which were eligible for analysis, reporting data on a total of 389 502 survivors. CCSs were less likely to complete higher levels of education (OR, 0.69; 95% CI, 0.40-1.18), had higher odds of health-related unemployment (OR, 2.94; 95% CI, 1.90-4.57), and showed lower rates of marriage (OR, 0.72; 95% CI, 0.63-0.84) and parenthood (OR, 0.60; 95% CI, 0.49-0.74) compared with population-based controls. Study findings suggest that CCSs face several socioeconomic difficulties; as a result, the next goal of pediatric oncology should be to minimize adverse effects, as well as to provide lifelong survivorship support aimed at maximizing social reintegration.

Use of Microbial L-asparaginase in Cancer Treatment -A Detail Review

Abstract The exceptional anticancer effects of l-asparaginases, which hydrolyze plasma l-asparagine and l-glutamine, have drew a lot of interest in recent years. This enzyme is effective against acute lymphoblastic leukemia (ALL) and lymphosarcoma, as well as ALL in children, neoplasia, and various other cancer .The l-asparaginase anticancer application technique has achieved amazing advances in modern oncology by depleting plasma l-asparagine to suppress cancer cell development, notably in youngsters. As bacterial alternative enzyme sources for anticancer therapy, high levels of l-asparaginase enzyme production by Escherichia coli, Erwinia species, Streptomyces, and Bacillus subtilis species are very desirable. Purification of L-asparaginase by Ammonium Sulphate precipitation and various chromatographic technique methods, and improvement of enzyme purity by dialysis confirmation of molecular weight with SDS page.

QIM24-177: Effects of a Music-Based Intervention on Reducing Compassion Fatigue in Oncology Advanced Practice Providers.

QIM24-177: Effects of a Music-Based Intervention on Reducing Compassion Fatigue in Oncology Advanced Practice Providers.

A Vision for Democratizing Next-Generation Oncology Clinical Trials.

Revolutionary advancements in oncology have transformed lives, but the clinical trials ecosystem encounters challenges, including restricted access to innovative therapies and a lack of diversity in participant representation. A vision emerges for democratized, globally accessible oncology trials, necessitating collaboration among researchers, clinicians, patients, and policymakers to shift from converting complex, exclusive trials into a dynamic, inclusive force against cancer.

Comprehensive Review on Recent Strategies for Management of Prostate Cancer: Therapeutic Targets and SAR.

Prostate cancer is a disease that is affecting a large population worldwide. Androgen deprivation therapy (ADT) has become a foundation for the treatment of advanced prostate cancer, as used in most clinical settings from neo-adjuvant to metastatic stage. In spite of the success of ADT in managing the disease in the majority of men, hormonal manipulation fails eventually. New molecules are developed for patients with various hormone-refractory diseases. Advancements in molecular oncology have increased understanding of numerous cellular mechanisms which control cell death in the prostate and these insights can lead to the development of more efficacious and tolerable therapies for carcinoma of the prostate. This review is focused on numerous therapies that might be a boon for prostate therapy like signaling inhibitors, vaccines, and inhibitors of androgen receptors. Along with these, various bioactive molecules and their derivatives are highlighted, which act as potential antiprostate cancer agents. This article also emphasized the recent advances in the field of medicinal chemistry of prostate cancer agents.

Machine learning analysis reveals tumor stiffness and hypoperfusion as biomarkers predictive of cancer treatment efficacy

In the pursuit of advancing cancer therapy, this study explores the predictive power of machine learning in analyzing tumor characteristics, specifically focusing on the effects of tumor stiffness and perfusion (i.e., blood flow) on treatment efficacy. Recent advancements in oncology have highlighted the significance of these physiological properties of the tumor microenvironment in determining treatment outcomes. We delve into the relationship between these tumor attributes and the effectiveness of cancer therapies in preclinical tumor models. Utilizing robust statistical methods and machine learning algorithms, our research analyzes data from 1365 cases of various cancer types, assessing how tumor stiffness and perfusion influence the efficacy of treatment protocols. We also investigate the synergistic potential of combining drugs that modulate tumor stiffness and perfusion with standard cytotoxic treatments. By incorporating these predictors into treatment planning, our study aims to enhance the precision of cancer therapy, tailoring treatment to individual tumor profiles. Our findings demonstrate a significant correlation between stiffness/perfusion and treatment efficacy, highlighting a new way for personalized cancer treatment strategies.

Need for a paradigm shift? Survival post-pancreatoduodenectomy remains poor despite surgical and oncological advances

Background: Despite advances in surgical techniques and chemotherapy, poor outcomes persist in pancreatic malignancy. This study aimed to investigate clinical outcomes and describe the impact of factors like the closest resection margin on overall survival following open pancreatoduodenectomy at a tertiary referral centre over a ten-year period. Methods: Patients who underwent a pancreaticoduodenectomy at a tertiary hospital in South Australia between 2009-2019 were included in this retrospective study. Patient demographics, systemic treatments, complications, and histological features were analysed for their role in overall survival. Kaplan-Meier survival curves were used to assess patient survival and estimate median survival time. Results: There were 134 open pancreaticoduodenectomy procedures during 2009-2019. Majority of patients were male (54.7%) between 65-75 years of age (41%) with an ASA physical status classification grade of 3 (63.3%). 56.7% of patients experienced a complication with 5 in-hospital deaths recorded and 12 ISPGF grade B or C pancreatic anastomotic leaks (n=5, n=7 respectively). 88% of resected specimens were malignant with an overall 5-year survival of 32%. A resection margin of >2 mm had a significantly improved overall survival compared to 0 mm (p=0.01). There was no survival benefit for a resection margin of <1 mm or 1-2 mm compared 0mm margin (p=0.6 and p=0.2 respectively). 65 patients (54.6%) experienced either local or distal disease recurrence by the end of the study period. Conclusions: There has been no improvement in overall survival post pancreatoduodenectomy for pancreatic malignancy. Further research into the clinical significance of the R status classification is required.

Multimodal therapy for metastatic colorectal cancer: a case of complete clinical and radiological response of liver metastases

Background. Colorectal cancer is one of the most common cancers and the second leading cause of cancer-related deaths worldwide. Population-based studies have shown that 25–30 % of patients with colorectal cancer have synchronous liver metastases at the time of diagnosis. despite modern advances in oncology and surgery, only 25 % of patients with metastatic colorectal cancer (mCRC) are suitable for liver resection, which is the only curative treatment option for these patients. In recent years, the indications for curative treatment of mCRC have expanded. due to the introduction of new targeted drugs into clinical practice, the tumor response rate to preoperative therapy has increased, thus increasing surgical resection rate. Some patients experience a complete clinical response, which is defined as the complete disappearance of liver metastases. However, 30–70 % of patients develop recurrent metastases in the liver within the first year of follow-up, and currently, even in the presence of complete regression of metastases, it is recommended to perform resection of the initially affected hepatic segments. Case presentation. We describe a case of complete clinical and radiological response of liver metastases after chemotherapy in a patient with sigmoid colon cancer. Molecular genetic analysis revealed the wild type of the Kras, Nras and Braf genes. The patient received 3 courses of preoperative chemotherapy according to the FOLFOxIRI + Cetuximab regimen. Laparoscopic sigmoid colon resection with d3 lymph node dissection was followed by adjuvant chemotherapy with oxaliplatin and 5-fluorouracil (12 cycles). After 16 months of follow-up, no evidence of colon cancer recurrence and liver metastasis was found. Conclusion. Current targeted therapy has demonstrated efficacy in treating mCRC with synchronous liver metastases and makes it possible, in selected cases, to avoid the liver resection provided that a complete clinical and radiological response of the metastases is achieved.

Abstract 4919: AI-enabled hit selection of drug screening on human pancreatic cancer organoids

Abstract Cancer remains one of the leading causes of death in the 21st century. Despite the latest advances in oncology, most cancer patients lack tailored therapeutic approaches with lasting benefit. Measuring the impact of anticancer compounds and their combinations is only possible on ex vivo assays. To this end, patient-derived organoids (PDOs) have been proposed as viable and efficient models for ex vivo testing. PDOs show long-term expansion potential while retaining tumor histopathology as well as cancer gene mutations. However, the translation of organoids in screening applications has so far been hampered by the lack of homogeneity and difficulties in handling and automation. Moreover, organoids are typically randomly distributed across the culture which complicates imaging and images analyses. To overcome these challenges, we set up a compound screening workflow with PDOs using Gri3D platform, comprising plates with micro-cavities suitable for high-throughput and reproducible organoid culture. Based on a standard 96 microtiter plate, each well contains a microwell array patterned in a cell repellent hydrogel. On Gri3D®, organoids are robustly generated in the microwells and are located in the same imaging plane. This greatly facilitates quantitative analyses in high content image-based screens. Furthermore, the pipetting port enables automation of cell seeding, media exchange and compound incubation with liquid-handlers, thus increasing assay reproducibility. In the presented work, we exposed human pancreatic cancer PDOs to a panel of anti-cancer compounds at different doses and followed their response to the drugs using viability dyes Calcein AM (live stain) and Ethidium Homodimer-1 (dead stain) with high-content confocal imaging. Using an AI-based approach, we efficiently detected each single organoid and extracted phenotypic features from all three channels (TL, live stain and dead stain) which correlate with cytotoxicity. The extracted features (more than 100) were first dimensionally reduced to 3 components using either PCA or UMAP, the treatments were then visualized in 3D scatter plots, ranked and clustered using machine learning. The data suggests that the compound treatment Palbociclib 50uM has significant cytotoxicity effects similar to the positive control, which is consistent with the traditional live/dead analysis. The AI approach demonstrates feasibility to perform drug screening in a robust and un-biased data analysis approach. Citation Format: Zhisong Tong, Angeline Lim, Marine Meyer, Maria Clapes, Oksana Sirenko, Nathalie Brandenberg. AI-enabled hit selection of drug screening on human pancreatic cancer organoids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4919.

Abstract 1761: Comprehensive profiling of the FAT3-associated gene signature in deciphering immunophenotypes of gastrointestinal cancers: Analysis of institutional cohort and TCGA dataset

Abstract Gastrointestinal (GI) cancers are among the most prevalent cancers affecting the US population. Anatomically, GI cancer includes cancers of the organs in the digestive tract, from the esophagus to the rectum. Advances in molecular oncology have started to transform the therapeutic landscape and offer tremendous promise for patients across diverse lineages. However, the equitable benefit of this approach has been hampered due to tumor heterogeneity and the lack of accurate, tumor-agnostic biomarkers with prognosis and predictive utility. Thus, there is a need to identify novel biomarkers that affect gastrointestinal malignancies to improve the management of cancer patients. This study analyzed a single institution's whole genome sequencing dataset to explore the genomic variation in GI cancers. Between 2020 and 2022, 302 AU patients underwent molecular profiling, including whole-exome sequencing (WES) profiling at Caris Life Sciences. WES is an NGS assay that analyzes the DNA sequences of all protein-coding exons in the genome, representing approximately 1-2% of the human genome with coverage of over 22,000 genes. We analyzed the TCGA dataset for comparative analysis, which included cancer data from >1800 GI cancer patients. In addition, survival and network analyses were performed to identify a 6-gene FAT3-related signature for GI cancers. In our cohort, we identified FAT3 (Fat atypical cadherin 3) as the most frequently mutated gene after TP53, APC, and KRAS. FAT3 encodes a cadherin protein involved in cell-cell interactions and adhesion. In the institutional cohort, FAT3 was found to be mutated in 16% of all GI cases. Further analysis of TCGA datasets comprising 1808 GI cancer patients revealed FAT3 mutations in 12% of the cases. To identify additional prognostic biomarkers associated with FAT3, we performed network analysis and identified a 6-gene FAT3-related signature (FAT3, RYK, FAT2, EGFLAM, NTRK3, IGSF9, and HMGA2) that significantly stratified GI cancer patients based on overall survival, progression-free survival, and disease-specific survival. The perturbation profile of the 6-gene signature was associated with 509 patients or 28% of total GI patients. Further, immune deconvolution analysis of stratified patients revealed increased infiltration of immune cells with immunosuppressive phenotypic properties in GI cancer patients with higher expression of the FAT3-related gene signature. In summary, this analysis reveals the distribution of FAT3 mutational profiles in GI patients and identifies a gene signature that stratifies patients based on survival outcomes. This analysis can provide new tools for patient stratification and therapy implementation, leading to better outcomes for cancer patients. Citation Format: Pankaj Kumar Ahluwalia, Tiffanie Leeman, Ashis Mondal, Ashutosh Vashisht, Harmanpreet Singh, Ravindra Kolhe. Comprehensive profiling of the FAT3-associated gene signature in deciphering immunophenotypes of gastrointestinal cancers: Analysis of institutional cohort and TCGA dataset [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1761.

Abstract 2554: Development/validation of a molecular and clinical evidence-based algorithm for selecting optimal precision therapeutic strategy for cancer patients - continuous study

Abstract Background: The integration of genotyping and genomics in clinical practice has brought about significant advancements in precision oncology. However, a persistent challenge for treating oncologists lies in selecting the most effective patient-specific therapeutic strategy due to the molecular rationale, disease relevance, and patient-specific issues. To address this challenge, we have developed an algorithm that incorporates both molecular and clinical evidence-based criteria to rank therapeutic strategies in order to deliver optimal care and improve outcomes in patients with malignancy. The purpose of this part of our studies was to evaluate the effectiveness and accuracy of our novel algorithm. Methods: History of present illness and comprehensive genomic profiling results of 306 patients with malignant tumors were reviewed by Avera Molecular Tumor Board (MTB) from June 2021 to February 2023. Therapeutic recommendations were provided with the Matching Score that we used in the I-PREDICT study based on molecular matching only as well as with the Ranking Score calculated by our novel algorithm with the criteria not only focusing on molecular matching, but also including disease relevance, patient-specific clinical considerations and treatment availability as weighting factors (Cohort 2). The other 50 patients with previously treated solid tumors reviewed by MTB (before 2018) and treatment recommendations provided with Matching Score only, were used as a control group (Cohort 1). The matching rates from recommendations and treatment outcomes of the patients were then assessed. Results: In Cohort 1, of the 50 patients, 33 patients (66%) received matched therapeutic plans recommended by our MTB. The other 17 patients were not on a matched plan from the MTB. At 12 weeks, 12 patients (36.4% of 33 patients) remained progression free, including 8 patients (24.2%) who were progression free at 6 months. The other 21 patients (63.6% of 33 patients) could not be assessed due to treatment termination per drug toxicity or death before the follow-up time point. The median PFS/overall survival (OS) for patients with a Matching Score > 50% (N = 17) were 7.5/10.5 months, whereas with Matching Score ≤ 50% (N = 16) were 3/7.35 months. In Cohort2, of the 306 patients, 130 (42.5 %) patients have initiated matched therapeutic plans and follow-up is ongoing. Updated results will be presented at the meeting. Conclusion: Our novel molecular and clinical evidence-based algorithm may be used to support oncologists’ decision-making to utilize the most clinically appropriate and effective therapeutic options to benefit patients. Further validation studies and development of a user-friendly computational ranking platform based on the algorithm are planned in order. Citation Format: Yuliang Sun, Tobias Meissner, Rachel Elsey, Crystal Hattum, Casey Williams. Development/validation of a molecular and clinical evidence-based algorithm for selecting optimal precision therapeutic strategy for cancer patients - continuous study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2554.