Precision Oncology Approaches Research Articles

Organoid-based precision medicine in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) ranks among the leading causes of cancer-related deaths worldwide. Despite advances in precision oncology in other malignancies, treatment of PDAC still largely relies on conventional chemotherapy. Given the dismal prognosis and heterogeneity in PDAC, there is an urgent need for personalized therapeutic strategies to improve treatment response. Organoids, generated from patients' tumor tissue, have emerged as a powerful tool in cancer research. These three-dimensional models faithfully recapitulate the morphological and genetic features of the parental tumor and retain patient-specific heterogeneity. This review summarizes existing precision oncology approaches in PDAC, explores current applications and limitations of organoid cultures in personalized medicine, details preclinical studies correlating in vitro organoid prediction and patient treatment response, and provides an overview of ongoing organoid-based clinical trials.

EXTH-72. INTEGRATED MULTIOMIC ANALYSIS OF ISOGENIC EGFRVIII MODELS OF GBM REVEALS EXPLOITABLE THERAPEUTIC VULNERABILITIES

Abstract Glioblastoma (GBM) is the most common primary malignant brain tumor with an abysmal 15-month median survival. Therefore, novel therapeutic interventions are urgently needed. EGFR is a receptor tyrosine kinase that is mutated in over 50% of GBM and is a logical target for precision oncology approaches. While aberrant EGFR signaling has been successfully targeted in other cancers, early attempts to target EGFR in GBM clinical trials have not been successful. Since these early trials, several studies have revealed that GBM EGFR biology is unique and cannot be generalized from other EGFR-driven neoplasms. To better understand EGFR biology in a GBM-specific context, we have characterized the GBM transcriptome with RNAseq, the epigenome with CUT&RUN, and the kinase proteome with Multiplexed inhibitor beads with Mass Spectrometry (MIB-MS), collectively referred to as ‘multiomics’, after modeling EGFR resistance. An isogenic mouse astrocyte (mAc) model of GBM was genetically engineered to overexpress EGFRvIII (CEv3), the most common EGFR mutation in GBM. Expression of EGFRvIII induces a unique multiomic profile that mediates many hallmark cancer phenotypes including proliferation and stemness. Chronic EGFR resistance was modeled both in vitro and in vivo through continuous exposure to erlotinib or gefitinib, EGFR tyrosine kinase inhibitors (TKI). Additionally, acute EGFR resistance was modeled using a single exposure to EGFR TKI afatinib or neratinib in vitro over a 48-hour time course. Preliminary multiomic characterization of these data has revealed several targets that can be further investigated for therapeutic exploitation. Further investigation into these targets using orthotopic allografts with CEv3 cells shows that combinatorial therapy with neratinib and abemacilib, a CDK inhibitor, significantly (p < 0.001, n= 20 mice per group) extends survival (56 days) compared to neratinib alone (31.5 days). Future integrated multiomic analysis aims to elucidate the synergistic relationship between neratinib and abemacilib.

The Evolving Molecular Landscape and Actionable Alterations in Urologic Cancers.

The genetic landscape of urologic cancers has evolved with the identification of actionable mutations that impact diagnosis, prognosis, and therapeutic strategies. This narrative review consolidates existing literature on genetic mutations across key urologic cancers, including bladder, renal, prostate, upper tract urothelial, testicular, and penile. The review highlights mutations in DNA damage repair genes, such as BRCA1/2 and PTEN, as well as pathway alterations like FGFR and PD-L1 overexpression. These mutations influence tumor behavior and therapeutic outcomes, emphasizing the need for precision oncology approaches. Molecular profiling, through tools like next-generation sequencing, has revolutionized patient care by enabling targeted treatment strategies, especially in cancers with distinct molecular subtypes such as luminal or basal bladder cancer and clear cell renal carcinoma. Emerging therapies, including FGFR inhibitors and immune checkpoint blockade, offer new treatment avenues, although resistance mechanisms remain a challenge. We also emphasize the importance of biomarker identification for personalized management, especially in metastatic settings where treatment intensification is often required. Future research is needed to further elucidate our understanding of the genetics affecting urologic cancers, which will help develop novel, individualized therapies to enhance oncologic outcomes.

Theranostic potential of miRNAs in oral cancer: An emerging approach for precision oncology

AbstractMicroRNAs (miRNAs) have emerged as pivotal regulators in the pathogenesis of oral cancer, offering promising diagnostic and therapeutic opportunities in precision oncology. Dysregulated miRNA expression profiles are reliable biomarkers for oral cancer diagnosis and prognosis. Specific miRNAs, including miR‐21, miR‐31, miR‐375, miR‐let‐7a, miR‐125a, and miR‐200c, show altered expression patterns linked to oral cancer diagnosis, staging, and prognosis. Furthermore, these differentially expressed miRNAs can be detected in readily available biofluids such as saliva and plasma, improving their utility as non‐invasive diagnostic tools. Aberrant miRNA expression contributes to crucial oncogenic pathways in oral cancer progression, metastasis, and drug resistance. Using miRNA mimics or anti‐miRNAs to manipulate miRNA expression provides a mechanism for influencing downstream target genes and sensitizing cancer cells to conventional chemotherapy or targeted therapies. Preclinical studies have demonstrated the efficiency of miRNA‐based therapeutics in suppressing the development of oral cancer cells and triggering apoptosis. Furthermore, miRNAs have been linked to medication resistance, opening up new options for improving therapy response in patients with oral cancer. Further research and clinical validation are warranted to fully exploit the theranostic potential of miRNAs in oral cancer management and advance precision oncology.

Artificial Intelligence in Cancer Research: Predictive Modeling of Angiogenesis and Biomarker Discovery

Background: The integration of Artificial Intelligence (AI) in cancer research has dramatically enhanced the study, diagnosis, and treatment of cancer. AI’s advanced algorithms, especially recurrent neural networks (RNNs), have proven effective in analyzing complex datasets, facilitating novel biomarker discovery, and improving cancer diagnostics and prognostics. Angiogenesis, the process of new blood vessel formation, plays a crucial role in tumor growth and metastasis, making it a promising target for therapeutic strategies. This study explores the use of AI to identify angiogenesis-related biomarkers and develop personalized treatment strategies. Methods: This study utilized a large dataset from The Cancer Genome Atlas (TCGA), encompassing over 20,000 primary tumor and normal samples across 33 cancer types. Preprocessing techniques such as data cleaning, normalization, and outlier detection were applied. Dimensionality reduction through Principal Component Analysis (PCA) and data visualization using t-Distributed Stochastic Neighbor Embedding (t-SNE) were employed. A Recurrent Neural Network (RNN) was chosen to analyze the sequential biological data and identify potential biomarkers related to angiogenesis. Results: The AI model demonstrated excellent performance across multiple evaluation metrics, including accuracy (0.85), precision (0.82), recall (0.88), F1-score (0.85), and AUC-ROC (0.92), highlighting its effectiveness in predicting cancer progression and identifying key biomarkers. The RNN model was particularly adept at identifying complex patterns in angiogenesis data, facilitating a deeper understanding of tumor biology and revealing novel therapeutic targets. Conclusion: The results underscore the significant potential of AI, specifically RNNs, in advancing cancer research and personalized treatment planning. AI-driven insights into angiogenesis-related biomarkers enable targeted therapies, offering new avenues for effective cancer treatment. These findings not only improve cancer diagnosis and prognosis but also emphasize the role of AI in developing precision oncology approaches, enhancing patient outcomes, and guiding future research in cancer therapeutics.

Chemoprevention of Head and Neck Cancer: A Review of Current Approaches and Future Perspectives.

Head and neck squamous cell carcinoma (HNSCC) is a spectrum of heterogeneous malignancies. A variety of genetic, environmental, and lifestyle factors contribute to the development of HNSCC. Carcinogenesis is a multistep process in which cell proliferation-associated oncogenes and cell-cycle regulation-associated tumor suppressor genes are dysregulated, resulting in premalignant lesions. Immune evasion is a critical step in the progression of benign lesions to advanced cancer. This review discusses the advances that have been made in chemoprevention strategies for HNSCC. The rationale for the use of chemopreventive agents to inhibit head and neck cancer development is highlighted by the positive outcomes of several clinical trials. We discuss the potential of some of the commonly studied agents including vitamin A analogs, EGFR inhibitors, COX-2 inhibitors, metabolic modulators, and natural compounds such as green tea, as well as immunotherapy and photodynamic therapy to prevent HNSCC. Our review provides insight into the potential benefits of these agents and the gaps that remain to be addressed. The published results reaffirm the promise of chemoprevention in head and neck cancer and suggest that continued exploration is needed to overcome the limitations. Because the current focus on chemopreventive agents is limited, major efforts in precision oncology approaches and substantial increase in funding will promote research into chemoprevention, which will eventually decrease the incidence of HNSCC.

Increased Synthetic Cytotoxicity of Combinatorial Chemoradiation Therapy in Homologous Recombination Deficient Tumors

BackgroundHomologous recombination deficient (HRD) tumors are exquisitely sensitive to platinum-based chemotherapy and when combined with RT, leads to improved overall survival in multiple cancer types. Whether a subset of tumors with distinct molecular characteristics demonstrate increased benefit from cisplatin and RT (c-RT) is unclear. We hypothesized that HRD tumors, whether associated with BRCA mutations or genomic scars of HRD, exhibit exquisite sensitivity to c-RT, and that HRD may be a significant driver of c-RT benefit. MethodsSensitivity to c-RT was examined using isogenic and sporadic breast cancer cell lines. HRD was assessed using four assays: RT-induced Rad51 foci, a DR-GFP reporter assay, a genomic scar (large scale state transitions, LST), and clonogenic survival assays (CSA). Whole genome sequencing of 4 breast tumors from a phase 2 clinical trial of neoadjuvant c-RT in triple negative breast cancer (TNBC) was performed and defined HRD utilizing HRDetect. ResultsBRCA1/2 deficient cell lines displayed functional HRD based on the Rad51 functional assay, with c-RT to RT or cisplatin interaction ratios (IR) of 1.11 and 26.84 for the BRCA1 isogenic pair at 2uM Cisplatin and 6Gy, respectively. The highest LST lines demonstrated HRD and synthetic cytotoxicity to c-RT with IR at 2Gy and Cisplatin 20uM of 7.50, and the lowest LST line with IR of 0.65. Of 4 evaluable patients on the Phase 2 trial, one achieved pathologic complete response (pCR) with corresponding HRD based on multiple genomic scar scores including HRDetect and LST scores, compared with patients without pCR. ConclusionsHRD breast cancers, whether identified by BRCA1/2 mutation status, functional tests or mutational signatures, appear to be significantly more sensitive to c-RT compared to isogenic controls or tumors without HRD mutational signature. HRD tumors may be exquisitely sensitive to c-RT and warrants further clinical investigation to guide a precision oncology approach.

DNA methylation signatures provide novel diagnostic biomarkers and predict responses of immune therapy for breast cancer.

Breast cancer (BRCA) is one of the most common malignant tumors affecting women worldwide. DNA methylation modifications can influence oncogenic pathways and provide potential diagnostic and therapeutic targets for precision oncology. In this study, we used non-parametric permutation tests to identify differentially methylated positions (DMPs) between paired tumor and normal BRCA tissue samples from the Cancer Genome Atlas (TCGA) database. Then, we applied non-negative matrix factorization (NMF) to the DMPs to derive eight distinct DNA methylation signatures. Among them, signatures Hyper-S3 and Hypo-S4 signatures were associated with later tumor stages, while Hyper-S1 and Hypo-S3 exhibited higher methylation levels in earlier stages. Signature Hyper-S3 displayed an effect on overall survival. We further validated the four stage-associated signatures using an independent BRCA DNA methylation dataset from peripheral blood samples. Results demonstrated that 24 commonly hypomethylated sites in Hypo-S4 showed lower methylation in BRCA patients compared to healthy individuals, suggesting its potential as an early diagnostic biomarker. Furthermore, we found that methylation of 23 probes from four stage-related signatures exhibited predictive power for immune therapy response. Notably, methylation levels of all three probes from the Hypo-S4 and activity of the Hypo-S4 demonstrated highly positive relevance to PD-L1 gene expression, implying their significant predictive values for immunotherapy outcomes. GO and KEGG pathway enrichment analysis revealed that genes with these 23 immunotherapy-related methylation probes are mainly involved in glycan degradation or protein deglycosylation. These methylation signatures and probes may serve as novel epigenetic biomarkers for predicting tumor immunotherapy response. Our findings provide new insights into precision oncology approaches for BRCA.

Renal Cell Carcinoma of Variant Histology: New Biologic Understanding Leads to Therapeutic Advances.

Renal cell carcinoma (RCC) is one of the 10 most commonly diagnosed solid tumors. Most RCCs are histologically defined as clear cell, comprising approximately 75% of diagnoses. However, the remaining RCC cases are composed of a heterogeneous combination of diverse histopathologic subtypes, each with unique pathogeneses and clinical features. Although the therapeutic approach to both localized and metastatic RCCs has dramatically changed, first with the advent of antiangiogenic targeted therapies and more recently with the approval of immune checkpoint inhibitor (ICI)-based combinations, these advances have primarily benefited the clear cell RCC patient population. As such, there remains critical gaps in the optimization of treatment regimens for patients with non-clear cell, or variant, RCC histologies. Herein, we detail recent advances in understanding the biology of RCC with variant histology and how such findings have guided novel clinical studies investigating precision oncology approaches for these rare subtypes. Among the most common variant histology RCCs are papillary RCC, comprising approximately 15%-20% of all diagnoses. Although a histopathologically diverse subset of tumors, papillary RCC is canonically associated with amplification of the MET protooncogene; recently completed and ongoing trials have investigated MET-directed therapies for this patient population. Finally, we discuss the unique biology of RCC with sarcomatoid dedifferentiation and the recent clinical findings detailing its paradoxical sensitivity to ICIs.

Therapeutic implications of phosphoproteomics in molecular cancer diagnostics.

3068 Background: Precision oncology approaches employing genomics-guided targeted therapies for individual patients have provided significant survival benefits in several cancer types. However, varying response rates in solid malignancies, many patients without actionable genomic lesions, and increasing evidence that non-genomic mechanisms may play an important role in tumors indicate that genomics alone is often insufficient to inform and guide the clinical care of patients. Since most targeted anti-cancer drugs inhibit the activity of protein kinases, measuring the tumor phosphoproteome as a direct readout of oncogenic pathway activity is poised to enhance molecular stratification. Methods: We established a clinical (phospho)proteomic workflow for integration into the molecular tumor board (MTB) workflow of the Germany-wide INFORM (for children with relapsed cancers) and MASTER (for young adults with refractory cancers and patients with rare tumors) registry studies and profiled > 1000 tumor tissue specimen from patients enrolled in the DKFZ/NCT/DKTK MASTER study or the INFORM registry trial. To assess the aberrant activity of druggable signaling pathways, we developed a new tumor pathway activity (TUPAC) scoring methodology using expression data of > 8,000 proteins and > 20,000 phospho-sites per patient in a heterogeneous pan-cancer cohort. TUPAC scores integrate protein expression and phosphopeptide abundance data at several levels to detect aberrant signaling pathway activities of several interdependent oncogenic signaling pathways within one tumor specimen. Results: We show for the first time that comprehensive (phospho)proteome profiling is feasible and informative in a real-world prospective precision oncology setting. Discussion of (phospho)proteomic data of > 500 prospective patients in weekly MTB meetings revealed that adding a (phospho)proteomic layer can supply critical information for personalized therapies that is not discernible from genomic and transcriptomic data. In an independent value evaluation (329 target recommendations in 104 patients), the phosphoproteome layer was decisive in 22% of all recommended targets. Based on anecdotal cases with available clinical follow-up, we provide evidence that (phospho)proteome profiling carries important diagnostic value by detecting actionable tumor-driving kinase signaling in patients without actionable genomic lesions or by functionalizing genomic variants of unknown significance. Conclusions: Measuring the tumor phosphoproteome as a direct readout of oncogenic pathway activity is feasible and adds complementary, therapy-relevant information in a real-world prospective precision oncology setting.

Combining germline, tissue and liquid biopsy analysis by comprehensive genomic profiling to improve the yield of actionable variants in a real-world cancer cohort

BackgroundComprehensive next-generation sequencing is widely used for precision oncology and precision prevention approaches. We aimed to determine the yield of actionable gene variants, the capacity to uncover hereditary predisposition and liquid biopsy appropriateness instead of, or in addition to, tumor tissue analysis, in a real-world cohort of cancer patients, who may benefit the most from comprehensive genomic profiling.MethodsSeventy-eight matched germline/tumor tissue/liquid biopsy DNA and RNA samples were profiled using the Hereditary Cancer Panel (germline) and the TruSight Oncology 500 panel (tumor tissue/cfDNA) from 23 patients consecutively enrolled at our center according to at least one of the following criteria: no available therapeutic options; long responding patients potentially fit for other therapies; rare tumor; suspected hereditary cancer; primary cancer with high metastatic potential; tumor of unknown primary origin. Variants were annotated for OncoKB and AMP/ASCO/CAP classification.ResultsThe overall yield of actionable somatic and germline variants was 57% (13/23 patients), and 43.5%, excluding variants previously identified by somatic or germline routine testing. The accuracy of tumor/cfDNA germline-focused analysis was demonstrated by overlapping results of germline testing. Five germline variants in BRCA1, VHL, CHEK1, ATM genes would have been missed without extended genomic profiling. A previously undetected BRAF p.V600E mutation was emblematic of the clinical utility of this approach in a patient with a liver undifferentiated embryonal sarcoma responsive to BRAF/MEK inhibition.ConclusionsOur study confirms the clinical relevance of performing extended parallel tumor DNA and cfDNA testing to broaden therapeutic options, to longitudinally monitor cfDNA during patient treatment, and to uncover possible hereditary predisposition following tumor sequencing in patient care.

Current state of theranostics in metastatic castrate-resistant prostate cancer.

Prostate cancer remains one of the leading causes of cancer-related death in the world. There have been significant advances in chemotherapy, hormonal therapy and targeted therapy options for patients with castrate-resistant disease. However, these systemic treatments are often associated with unwanted toxicities. Targeted therapy with radiopharmaceuticals has become of key interest to limit systemic toxicity and provides a more precision oncology approach to treatment. Strontium-89, Samarium-153 EDTMP and Radium-223 have been trialled with mixed results. Strontium-89 and Samarium-153 EDTMP have shown benefits in palliating metastatic bone pain but with no impact on survival outcomes. Early therapeutic radiopharmaceuticals targeting PSMA that were developed were beta-emitting agents, but recently alpha-emitting agents are being investigated as potentially superior options. Radium-223 is the first alpha-particle emitter therapeutic agent approved by the FDA, with phase III trial evidence showing benefits in overall survival and delay in symptomatic skeletal events for patients. Recently, 177-Lutetium-PSMA-617 has demonstrated significant survival advantages in pre-treated metastatic castrate-resistant cancer patients in a number of phase II and III studies. Furthermore, 225-Actinium-PSMA-617 also showed promise even in patients pre-treated with 177-Lutetium-PSMA-617. Hence, there has been an explosion of radiopharmaceutical treatment options for patients with prostate cancer. This review explores past and current theranostic capacities in the radiopharmaceutical treatment of metastatic castrate-resistant prostate cancer.

Roles of reactive oxygen species in inflammation and cancer.

Reactive oxygen species (ROS) constitute a spectrum of oxygenic metabolites crucial in modulating pathological organism functions. Disruptions in ROS equilibrium span various diseases, and current insights suggest a dual role for ROS in tumorigenesis and the immune response within cancer. This review rigorously examines ROS production and its role in normal cells, elucidating the subsequent regulatory network in inflammation and cancer. Comprehensive synthesis details the documented impacts of ROS on diverse immune cells. Exploring the intricate relationship between ROS and cancer immunity, we highlight its influence on existing immunotherapies, including immune checkpoint blockade, chimeric antigen receptors, and cancer vaccines. Additionally, we underscore the promising prospects of utilizing ROS and targeting ROS modulators as novel immunotherapeutic interventions for cancer. This review discusses the complex interplay between ROS, inflammation, and tumorigenesis, emphasizing the multifaceted functions of ROS in both physiological and pathological conditions. It also underscores the potential implications of ROS in cancer immunotherapy and suggests future research directions, including the development of targeted therapies and precision oncology approaches. In summary, this review emphasizes the significance of understanding ROS-mediated mechanisms for advancing cancer therapy and developing personalized treatments.

Computational repurposing of oncology drugs through off-target drug binding interactions from pharmacological databases.

Systematic repurposing of approved medicines for another indication may accelerate drug development in oncology. We present a strategy combining biomarker testing with drug repurposing to identify new treatments for patients with advanced cancer. Tumours were sequenced with the Illumina TruSight Oncology 500 (TSO-500) platform or the FoundationOne CDx panel. Mutations were screened by two medical oncologists and pathogenic mutations were categorised referencing literature. Variants of unknown significance were classified as potentially pathogenic using plausible mechanisms and computational prediction of pathogenicity. Gain of function (GOF) mutations were evaluated through repurposing databases Probe Miner (PM), Broad Institute Drug Repurposing Hub (Broad Institute DRH) and TOPOGRAPH. GOF mutations were repurposing events if identified in PM, not indexed in TOPOGRAPH and excluding mutations with a known Food and Drug Administration (FDA)-approved biomarker. The computational repurposing approach was validated by evaluating its ability to identify FDA-approved biomarkers. The total repurposable genome was identified by evaluating all possible gene-FDA drug-approved combinations in the PM dataset. The computational repurposing approach was accurate at identifying FDA therapies with known biomarkers (94%). Using next-generation sequencing molecular reports (n=94), a meaningful percentage of patients (14%) could have an off-label therapeutic identified. The frequency of theoretical drug repurposing events in The Cancer Genome Atlas pan-cancer dataset was 73% of the samples in the cohort. A computational drug repurposing approach may assist in identifying novel repurposing events in cancer patients with no access to standard therapies. Further validation is needed to confirm a precision oncology approach using drug repurposing.

Abstract 6414: Molecular differentiation between complete and incomplete responders to neoadjuvant therapy in rectal cancer

Abstract Neoadjuvant chemoradiotherapy (nCRT) is the standard treatment for locally advanced rectal cancer, but only 20-40% of patients completely respond to this treatment. This study aims to identify the molecular features associated with a response to nCRT. We generated and collected genomic and transcriptomic data from 712 cancers prior to treatment from our own data and from publicly available data. A comprehensive integrated analysis was performed. We found that patients with a complete response have decreased risk of both local recurrence and future metastasis. We identified multiple molecular differences between complete and incomplete responders. Complete responders have a higher tumor mutation burden and more significant co-occurring mutations than the incomplete responders. In addition, mutations in DNA repair genes were enriched in complete responders and they also had lower expression of these genes indicating that defective DNA repair is associated with complete response to nCRT. Using logistic regression, we identified three significant predictors of complete response: tumor size, mutations within specific network genes, and the existence of three or more specific co-occurrent mutations. In incompletely responder tumors, abnormal cell-cell interaction and increased cancer associated fibroblasts were associated with recurrence. Additionally, gene expression analysis identified a subset of immune hot tumors with worse outcomes and upregulation of immune checkpoint proteins. Our study directly informs the clinical management of rectal cancer by elucidating the molecular differences between tumors with complete and incomplete responses to neoadjuvant chemoradiotherapy (nCRT), as well as the features of tumors prone to recurrence. We have pinpointed critical molecular markers and clinical indicators—such as tumor size, specific gene mutations, and particular mutation patterns—that are significant predictors of treatment response. These findings offer valuable biomarkers for personalizing treatment strategies. Additionally, the observed mutation enrichment in DNA repair genes among complete responders suggests new avenues for therapeutic innovation. By highlighting the distinct molecular and immune profiles of non-responder tumors at higher recurrence risk, our research supports the advancement of precision oncology approaches, enhancing prognosis and treatment customization in rectal cancer care, ultimately striving to bridge the gap between scientific discovery and clinical application. Citation Format: Fengyuan Huang, M. Chandler McLeod, Regina Kay Irwin, Mary Smithson, Zongliang Yue, Min Gao, Karin M. Hardiman, Zechen Chong. Molecular differentiation between complete and incomplete responders to neoadjuvant therapy in rectal cancer [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 6414.

Moving from conventional to adaptive risk stratification for oropharyngeal cancer.

Oropharyngeal cancer (OPC) poses a complex therapeutic dilemma for patients and oncologists alike, made worse by the epidemic increase in new cases associated with the oncogenic human papillomavirus (HPV). In a counterintuitive manner, the very thing which gives patients hope, the high response rate of HPV-associated OPC to conventional chemo-radiation strategies, has become one of the biggest challenges for the field as a whole. It has now become clear that for ~30-40% of patients, treatment intensity could be reduced without losing therapeutic efficacy, yet substantially diminishing the acute and lifelong morbidity resulting from conventional chemotherapy and radiation. At the same time, conventional approaches to de-escalation at a population (selected or unselected) level are hampered by a simple fact: we lack patient-specific information from individual tumors that can predict responsiveness. This results in a problematic tradeoff between the deleterious impact of de-escalation on patients with aggressive, treatment-refractory disease and the beneficial reduction in treatment-related morbidity for patients with treatment-responsive disease. True precision oncology approaches require a constant, iterative interrogation of solid tumors prior to and especially during cancer treatment in order to tailor treatment intensity to tumor biology. Whereas this approach can be deployed in hematologic diseases with some success, our ability to extend it to solid cancers with regional metastasis has been extremely limited in the curative intent setting. New developments in metabolic imaging and quantitative interrogation of circulating DNA, tumor exosomes and whole circulating tumor cells, however, provide renewed opportunities to adapt and individualize even conventional chemo-radiation strategies to diseases with highly variable biology such as OPC. In this review, we discuss opportunities to deploy developing technologies in the context of institutional and cooperative group clinical trials over the coming decade.

Patient derived tumoroids of high grade neuroendocrine neoplasms for more personalized therapies

There are no therapeutic predictive biomarkers or representative preclinical models for high-grade gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN), a highly aggressive, fatal, and heterogeneous malignancy. We established patient-derived (PD) tumoroids from biobanked tissue samples of advanced high-grade GEP-NEN patients and applied this model for targeted rapid ex vivo pharmacotyping, next-generation sequencing, and perturbational profiling. We used tissue-matched PD tumoroids to profile individual patients, compared ex vivo drug response to patients’ clinical response to chemotherapy, and investigated treatment-induced adaptive stress responses.PD tumoroids recapitulated biological key features of high-grade GEP-NEN and mimicked clinical response to cisplatin and temozolomide ex vivo. When we investigated treatment-induced adaptive stress responses in PD tumoroids in silico, we discovered and functionally validated Lysine demethylase 5 A and interferon-beta, which act synergistically in combination with cisplatin. Since ex vivo drug response in PD tumoroids matched clinical patient responses to standard-of-care chemotherapeutics for GEP-NEN, our rapid and functional precision oncology approach could expand personalized therapeutic options for patients with advanced high-grade GEP-NEN.

The role of pre-operative ctDNA in resectable intrahepatic cholangiocarcinoma.

528 Background: Genomic profiling of circulating tumor DNA (ctDNA) is increasingly used in intrahepatic cholangiocarcinoma (iCCA) to inform precision oncology approaches and determine resistance mechanisms to targeted therapies. The application of pre-operative ctDNA testing in the management of iCCA for prognostication remains unclear. Methods: In this retrospective study, we analyzed pre-operative plasma samples from 14 patients who underwent curative resection for iCCA without neoadjuvant therapy. A personalized and tumor-informed assay (Signatera; Natera, Inc.) was used for the detection and quantification of ctDNA. We correlated ctDNA profiles with baseline tumour characteristics and clinical outcomes. Results: The mean interval between pre-operative blood collection and surgery was 43 days (range: 1 to 90 days). ctDNA was detected in all patients except for one with stage Ia (AJCC 8th) disease (Table). The mean pre-operative ctDNA concentration was lowest in the stage Ia group [4.2 mean tumor molecules (MTM)/mL] and highest in the stage II group (134.0 MTM/mL). The mean pre-operative ctDNA concentration did not exhibit a linear correlation with disease recurrence or mortality rates, however, it showed a moderate-to-good linear correlation with the largest pathologic tumor size (R2 = 0.55). Among the three patients who had IDH1/2 mutations tracked in the plasma by Signatera, two patients had positive IDH1/2 detection in ctDNA with mean ctDNA concentrations of 83.7 MTM/mL (range: 33.8 to 133.5 MTM/mL). The patient with the second-highest ctDNA concentration (133.5 MTM/mL and 1818 days follow-up) had stage Ib disease with an IDH1 mutation but has shown no evidence of recurrence. Conclusions: In the pre-operative setting for iCCA resections, ctDNA can be reliably detected across all disease stages using a tumor-informed approach, even when blood is collected up to 90 days before surgery. While single time-point pre-operative ctDNA concentration levels do not appear to correlate with outcomes, similar to previous reports in colon adenocarcinoma, they may correlate with tumor volume. Further studies are needed to evaluate the utility of tumor-informed ctDNA testing in the post-operative setting to detect molecular residual disease for improved prognostication. [Table: see text]

The future of collaborative precision oncology approaches in sub-Saharan Africa: learnings from around the globe.

As the projected incidence and mortality of cancer in Sub-Saharan Africa (SSA) rises to epidemic proportions, it is imperative that more is done to identify the genomic differences and commonalities between patients of African and European ancestry to fulfil the promise of precision oncology. Here, we summarize the utility of precision oncology approaches, with a focus on comprehensive genomic profiling (CGP) and consolidate examples of national and international consortia that are driving the field forward. We describe the importance of genomic diversity and its relevance in cancer, and propose recommendations, success factors and desired outcomes for precision oncology consortia to adopt in SSA. Through this, we hope to catalyze the initiation of such projects and to contribute to improving cancer patient outcomes in the region.

The Precision Oncology Approach to Molecular Cancer Therapeutics Targeting Oncogenic Signaling Pathways is a Means to an End

The Precision Oncology Approach to Molecular Cancer Therapeutics Targeting Oncogenic Signaling Pathways is a Means to an End