Genomic Alterations In Cancer Research Articles

439 Extracellular-in-frame deletions and kinase domain duplications are novel, gain-of-function mutations in fibroblast growth factor receptor genes in cancer

OBJECTIVES/GOALS: There are gain-of-function genomic alterations in FGFR genes that guide personalized treatment in some patients with cholangiocarcinoma (10%) and bladder cancer (30%) who can benefit from targeted therapies. We sought to evaluate other genomic alterations in cancer involving FGFRs and assess whether they are gain-of-function. METHODS/STUDY POPULATION: We collaborated with Foundation Medicine Inc (FMI), for the assessment of 300,000 sequenced tumors and a retrospective analysis of recent publications, to identify novel candidate FGFR alterations. We propose to transiently transfect HEK293T cells with an empty vector (EV), FGFR1-4 wild-type (WT), and these variants and use a luminescent-proximity based high-throughput assay, AlphaLISA, and Western blot to assess FGFR and phosphorylated downstream signaling proteins, FRS2, AKT and ERK, and their sensitivity to FGFR inhibitors: pemigatinib, erdafitinib, futibatinib, RLY-4008, and TYRA-200. RESULTS/ANTICIPATED RESULTS: Through our collaboration we identified >100 novel candidate FGFR1-4 variants of unknown significance (VUS) including extracellular-in-frame deletions (EIDs), kinase domain duplications (KDDs), insertions/deletions (INDELs), short number variants (SNVs), and truncations. Immunoblot analysis confirmed the presence of desired EV, FGFR WT, and VUS’ in HEK293T cells. We anticipate the FGFR EIDs and KDDs to display an increased presence of in the respective pFGFR, pFRS2, pERK, and pAKT as compared to the EV and FGFR WT by both immunoblot and AlpahLISA analysis. Additionally, we anticipate the VUS’ to be sensitive to FGFR inhibitors: pemigatinib, erdafitinib, futibatinib, RLY-4008, and TYRA-200 using the AlphaLISA assay. DISCUSSION/SIGNIFICANCE: These findings suggest that the novel FGFR VUS’ are capable of constitutive activation of FGFR kinase activity, and they preliminary demonstrate that these newly identified FGFR alterations are therapeutically targetable. Thus, providing rationale for further clinical evaluation to identify new cohorts of FGFR inhibitor responders.

Abstract 6599: 3D genomic analysis reveals novel enhancer hijacking mechanisms caused by complex structural alterations that drive oncogene overexpression

Abstract Enhancer hijacking, caused by structural alterations on chromosomes as well as extrachromosomal DNA (ecDNA), is a common cancer driver event. The complexity and ubiquity of structural alterations in cancer genomes make it difficult to identify enhancer hijacking with genome sequencing alone. Here we describe a 3D genomics-based analysis called HAPI (Highly Active Promoter Interactions) to characterize enhancer hijacking caused by various types of structural alterations. Applying HAPI analysis to HiChIP data from 34 cancer cell lines, we identified novel enhancers hijacked through chromosomal rearrangements to activate both known and potentially novel oncogenes such as MYC, CCND1, ETV1, CRKL, and ID4, which we validated using CRISPRi assays and RNA-seq analysis. Furthermore, we found that ecDNAs often contain multiple oncogenes from different chromosomes, which cause nested enhancer hijacking among them. For instance, we found that MYC ecDNAs relocate additional oncogenes from other chromosomes such as CDX2, ERBB2, or CD44 near the MYC locus, co-opting MYC’s enhancers for their overexpression, which we validated using dual-color DNA FISH and CRISPRi assays. This multiple oncogenes-involved enhancer hijacking mechanism may suggest novel therapeutic strategies such as targeting either the co-opting oncogenes or the hijacked enhancers for ecDNAs. Our study provides a robust strategy to detect enhancer hijacking events using our publicly available HAPI analysis tool and reveals novel mechanisms underlying oncogene activation caused by chromosomal and extrachromosomal structural alterations. Citation Format: Katelyn L. Mortenson, Courtney Dawes, Emily R. Wilson, Nathan E. Patchen, Hailey Johnson, Jason Gertz, Swneke D. Bailey, Yan Liu, Katherine E. Varley, Xiaoyang Zhang. 3D genomic analysis reveals novel enhancer hijacking mechanisms caused by complex structural alterations that drive oncogene overexpression [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 6599.

Clinical Management of Patients with Non-Small Cell Lung Cancer, Brain Metastases, and Actionable Genomic Alterations: A Systematic Literature Review.

Nearly 60% of patients with non-small cell lung cancer (NSCLC) present with metastatic disease, and approximately 20% have brain metastases (BrMs) at diagnosis. During the disease course, 25-50% of patients will develop BrMs. Despite available treatments, survival rates for patients with NSCLC and BrMs remain low, and their overall prognosis is poor. Even with newer agents for NSCLC, options for treating BrMs can be limited by their ineffective transport across the blood-brain barrier (BBB) and the unique brain tumor microenvironment. The presence of actionable genomic alterations (AGAs) is a key determinant of optimal treatment selection, which aims to maximize responses and minimize toxicities. The objective of this systematic literature review (SLR) was to understand the current landscape of the clinical management of patients with NSCLC and BrMs, particularly those with AGAs. A Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA)-compliant SLR was conducted to identify studies in patients with BrMs in NSCLC. Searches used the EMBASE and MEDLINE® databases, and articles published between January 1, 2017 and September 26, 2022 were reviewed. Overall, 179 studies were included in the SLR. This subset review focused on 80 studies that included patients with NSCLC, BrMs, and AGAs (19 randomized controlled trials [RCTs], two single-arm studies, and 59 observational studies). Sixty-four of the 80 studies reported on epidermal growth factor receptor (EGFR) mutations, 14 on anaplastic lymphoma kinase (ALK) alterations, and two on both alterations. Ninety-five percent of studies evaluated targeted therapy. All RCTs allowed patients with previously treated, asymptomatic, or neurologically stable BrMs; the percentage of asymptomatic BrMs varied across observational studies. Although targeted therapies demonstrate systemic benefits for patients with NSCLC, BrMs, and AGAs, there remains a continued need for effective therapies to treat and prevent BrMs in this population. Increased BBB permeability of emerging therapies may improve outcomes for this population.

Genomic Alterations Affecting Competitive Endogenous RNAs (ceRNAs) and Regulatory Networks (ceRNETs) with Clinical Implications in Triple-Negative Breast Cancer (TNBC).

The concept of competitive endogenous RNA regulation has brought on a change in the way we think about transcriptional regulation by miRNA-mRNA interactions. Rather than the relatively simple idea of miRNAs negatively regulating mRNA transcripts, mRNAs and other non-coding RNAs can regulate miRNAs and, therefore, broad networks of gene products through competitive interactions. While this concept is not new, its significant roles in and implications on cancer have just recently come to light. The field is now ripe for the extrapolation of technologies with a substantial clinical impact on cancer. With the majority of the genome consisting of non-coding regions encoding regulatory RNAs, genomic alterations in cancer have considerable effects on these networks that have been previously unappreciated. Triple-negative breast cancer (TNBC) is characterized by high mutational burden, genomic instability and heterogeneity, making this aggressive breast cancer subtype particularly relevant to these changes. In the past few years, much has been learned about the roles of competitive endogenous RNA network regulation in tumorigenesis, disease progression and drug response in triple-negative breast cancer. In this review, we present a comprehensive view of the new knowledge and future perspectives on competitive endogenous RNA networks affected by genomic alterations in triple-negative breast cancer. An overview of the competitive endogenous RNA (ceRNA) hypothesis and its bearing on cellular function and disease is provided, followed by a thorough review of the literature surrounding key competitive endogenous RNAs in triple-negative breast cancer, the genomic alterations affecting them, key disease-relevant molecular and functional pathways regulated by them and the clinical implications and significance of their dysregulation. New knowledge of the roles of these regulatory mechanisms and the current acceleration of research in the field promises to generate insights into the diagnosis, classification and treatment of triple-negative breast cancer through the elucidation of new molecular mechanisms, therapeutic targets and biomarkers.

Fragmentomics of cell-free DNA from targeted panels in genitourinary malignancies.

199 Background: The detection of genomic alterations in cancer is critical for identifying clinically actionable alterations for treatment decisions. Tumor samples historically have been required, but obtaining tissue for molecular profiling is not always feasible, especially in the metastatic setting. The isolation and analysis of cell-free DNA (cfDNA) including circulating tumor DNA (ctDNA) via blood-based “liquid” biopsies offers non-invasive sampling of the tumor. Recently, fragmentation patterns of cfDNA (i.e. “fragmentomics”) have emerged as a method for inferring epigenomic and transcriptomic information. However, these analyses use whole-genome sequencing, which lacks the necessary depth to cost-effectively assess genomic alterations, limiting the application of these techniques clinically. Methods: We developed a novel cfDNA fragmentomics machine learning approach for standard targeted cancer gene panels in order to identify genitourinary (GU) and non-GU cancers from two independent metastatic cancer cohorts: a published cohort from GRAIL (prostate cancer, non-GU cancers, normal samples, N=198) and an expanded institutional cohort from the University of Wisconsin (prostate adenocarcinoma, neuroendocrine prostate cancer (NEPC), renal cell carcinoma (RCC), bladder cancer, non-GU cancers, normal samples, n = 431). Results: In the GRAIL cohort, 10-fold cross-validation AUCs were 0.987 for identifying prostate cancer, 1.00 for normal samples, and ranged from 0.922-0.958 for the non-GU cancers. In the UW cohort, 10-fold cross-validation AUCs were 0.950 for bladder cancer, 0.982 for prostate cancer, 0.993 for NEPC, 0.925 for RCC, and 0.980 for normal samples, and ranged from 0.874-0.954 for non-GU cancers. Our assay can sensitively detect and accurately distinguish GU and non-GU malignancies despite a median ctDNA fraction of only 0.076 in the GRAIL cohort, and a median ctDNA fraction of only 0.022 in the UW cohort. Conclusions: Our enhanced machine learning approach for examining fragmentomics in standard cancer gene cfDNA panels unlocks the potential for these established assays to be utilized to answer critical clinical questions beyond somatic variant identification. The excellent performance of our innovative approach even in samples with low ctDNA fractions suggest potential applications such as multi-cancer early detection and minimal residual disease monitoring. This framework could dramatically expand the potential of already existing clinically used assays and minimizes barriers for continued biomarker development.

Integrated characterization of hepatobiliary tumor organoids provides a potential landscape of pharmacogenomic interactions

Despite considerable efforts to identify human liver cancer genomic alterations that might unveil druggable targets, the systematic translation of multiomics data remains challenging. Here, we report success in long-term culture of 64 patient-derived hepatobiliary tumor organoids (PDHOs) from a Chinese population. A divergent response to 265 metabolism- and epigenetics-related chemicals and 36 anti-cancer drugs is observed. Integration of the whole genome, transcriptome, chromatin accessibility profiles, and drug sensitivity results of 64 clinically relevant drugs defines over 32,000 genome-drug interactions. RUNX1 promoter mutation is associated with an increase in chromatin accessibility and a concomitant gene expression increase, promoting a cluster of drugs preferentially sensitive in hepatobiliary tumors. These results not only provide an annotated PDHO biobank of human liver cancer but also suggest a systematic approach for obtaining a comprehensive understanding of the gene-regulatory network of liver cancer, advancing the applications of potential personalized medicine.

Actionable mutational profiling in solid tumors using hybrid-capture-based next-generation sequencing in a real-world setting in Spain.

This study aimed to describe the performance of a next-generation sequencing (NGS) panel for the detection of precise genomic alterations in cancer in Spanish clinical practice. The impact of tumor characteristics was evaluated on informative NGS and actionable mutation rates. A cross-sectional study was conducted at the Fundación Jiménez Díaz University Hospital (May 2021-March 2022) where molecular diagnostic of 537 Formalin-Fixed Paraffin-Embedded (FFPE) tissue samples of diverse solid tumors (lung, colorectal, melanoma, gastrointestinal stromal, among others) was performed using AVENIO Tumor Tissue Targeted Kit. A descriptive analysis of the features of all samples was carried out. Multivariable logistic analysis was conducted to assess the impact of sample characteristics on NGS performance defined by informative results rate (for all tumors and for lung tumors), and on actionable mutations rate (for lung tumors only). AVENIO performance rate was 75.2% in all tumor samples and 75.3% in lung cancer samples, and the multivariable analysis showed that surgical specimens are most likely to provide informative results than diagnostic biopsies. Regarding the mutational findings, 727 pathogenic, likely pathogenic, or variant of unknown significance mutations were found in all tumor samples. Single nucleotide variant was the most common genomic alteration, both for all tumor samples (85.3% and 81.9% for all solid tumors and lung samples, respectively). In lung tumors, multivariable analysis showed that it is more likely to find actionable mutations from non-smokers and patients with adenocarcinoma, large cell, or undifferentiated histologies. This is the largest cohort-level study in Spain to profile the analyses of biopsy samples of different tumors using NGS in routine clinical practice. Our findings showed that the use of NGS routinely provides good rates of informative results and can improve tumor characterization and identify a greater number of actionable mutations.

Assessing the Expression of Long INterspersed Elements (LINEs) via Long-Read Sequencing in Diverse Human Tissues and Cell Lines.

Transposable elements, such as Long INterspersed Elements (LINEs), are DNA sequences that can replicate within genomes. LINEs replicate using an RNA intermediate followed by reverse transcription and are typically a few kilobases in length. LINE activity creates genomic structural variants in human populations and leads to somatic alterations in cancer genomes. Long-read RNA sequencing technologies, including Oxford Nanopore and PacBio, can directly sequence relatively long transcripts, thus providing the opportunity to examine full-length LINE transcripts. This study focuses on the development of a new bioinformatics pipeline for the identification and quantification of active, full-length LINE transcripts in diverse human tissues and cell lines. In our pipeline, we utilized RepeatMasker to identify LINE-1 (L1) transcripts from long-read transcriptome data and incorporated several criteria, such as transcript start position, divergence, and length, to remove likely false positives. Comparisons between cancerous and normal cell lines, as well as human tissue samples, revealed elevated expression levels of young LINEs in cancer, particularly at intact L1 loci. By employing bioinformatics methodologies on long-read transcriptome data, this study demonstrates the landscape of L1 expression in tissues and cell lines.

Topological reorganization and functional alteration of distinct genomic components in gallbladder cancer.

Altered three-dimensional architecture of chromatin influences various genomic regulators and subsequent gene expression in human cancer. However, knowledge of the topological rearrangement of genomic hierarchical layers in cancer is largely limited. Here, by taking advantage of in situ Hi-C, RNA-sequencing, and chromatin immunoprecipitation sequencing (ChIP-seq), we investigated structural reorganization and functional changes in chromosomal compartments, topologically associated domains (TADs), and CCCTC binding factor (CTCF)-mediated loops in gallbladder cancer (GBC) tissues and cell lines. We observed that the chromosomal compartment A/B switch was correlated with CTCF binding levels and gene expression changes. Increased inter-TAD interactions with weaker TAD boundaries were identified in cancer cell lines relative to normal controls. Furthermore, the chromatin short loops and cancer unique loops associated with chromatin remodeling and epithelial-mesenchymal transition activation were enriched in cancer compared with their control counterparts. Cancer-specific enhancer-promoter loops, which contain multiple transcription factor binding motifs, acted as a central element to regulate aberrant gene expression. Depletion of individual enhancers in each loop anchor that connects with promoters led to the inhibition of their corresponding gene expressions. Collectively, our data offer the landscape of hierarchical layers of cancer genome and functional alterations that contribute to the development of GBC.

Spatial and clonality-resolved 3D cancer genome alterations reveal enhancer-hijacking as a potential prognostic marker for colorectal cancer

The regulatory effect of non-coding large-scale structural variations (SVs) on proto-oncogene activation remains unclear. This study investigated SV-mediated gene dysregulation by profiling 3D cancer genome maps from 40 patients with colorectal cancer (CRC). We developed a machine learning-based method for spatial characterization of the altered 3D cancer genome. This revealed a frequent establishment of "de novo chromatin contacts" that can span multiple topologically associating domains (TADs) in addition to the canonical TAD fusion/shuffle model. Using this information, we precisely identified super-enhancer (SE)-hijacking and its clonal characteristics. Clonal SE-hijacking genes, such as TOP2B, are recurrently associated with cell-cycle/DNA-processing functions, which can potentially be used as CRC prognostic markers. Oncogene activation and increased drug resistance due to SE-hijacking were validated by reconstructing the patient's SV using CRISPR-Cas9. Collectively, the spatial and clonality-resolved analysis of the 3D cancer genome reveals regulatory principles of large-scale SVs in oncogene activation and their clinical implications.

Comprehensive genomic profiling before the first-line setting versus after the completion of standard of care in patients with previously untreated advanced solid tumors: The prospective FIRST-Dx study.

3111 Background: Precision oncology using the comprehensive genomic profiling (CGP) test by next-generation sequencing has been introduced into clinical practice. In Japan, only 6.8% of patients accessed the precision treatment because it is only indicated after standard of care (SoC). FoundationOne CDx (F1CDx) is the software as a medical device for the detection of actionable and druggable genomic alterations in 324 genes. F1CDx has the function of both CGP test and companion diagnostics (CDx). Therefore, F1CDx could be ideally used in the early stages of treatments. In this study, we investigated the clinical utility of F1CDx in previously untreated patients with metastatic or recurrent solid tumors. Methods: We conducted a multi-institutional, prospective study in six hospitals in Japan (FIRST-Dx study). Chemotherapy-naïve adult patients with advanced solid tumor (GI, Lung, Breast, GYN, Melanoma) and ECOG performance status of 0-1 were enrolled. Primary endpoint was the ratio of patients with actionable mutation. Secondary endpoints were the ratio of patients with druggable mutation, molecular-based recommended therapy (MBRT), gene alteration with CDx, CGP success rate, and patients who actually received MBRT. Results: 183 patients were enrolled between May 2021 and February 2022, 180 patients with median (range) age 64 (23-88) years underwent F1CDx test (92 men, lung [n=28], colon/small intestine [n=27], pancreas [n=27], breast [n=25], biliary tract [n=20], gastric [n=19], uterus [n=12], esophagus [n=10], ovary [n=6], and skin melanoma [n=6]). 175 tests were successful (CGP success rate: 97%), and 172 patients were evaluable for endpoint analyses with follow-up through July 2022. Actionable and druggable cancer genomic alterations were found in 172 patients (100.0% [95% CI: 97.9-100.0%]) and 109 patients (63.4% [95% CI: 55.7-70.6%]), respectively. MBRT determined by molecular tumor board was found in 105 patients (61.0% [95% CI: 53.3-68.4%]). Genomic alterations included in the CDx list of F1CDx were found in 49 patients (28.5% [95%CI: 21.9-35.9%]) in the tumor-agnostic setting. After a median follow-up of 7.9 months, 34 patients (19.8 % [95%CI: 14.1-26.5%]) actually received MBRTs. Twenty-six patients received evidence level A MBRT, two received evidence level B MBRT, and six received evidence level C MBRT. Conclusions: We showed that 61% of the patients with previously untreated advanced cancer had MBRTs found by F1CDx and 20% of them actually received MBRTs early in their disease course. CGP test before SoC for advanced solid tumors could provide better opportunities for receiving MBRTs than after completion of SoC. Our data would recommend expanded approval with respect to the timing of CGP test for patients with previously untreated advanced solid tumors. Clinical trial information: UMIN000042408 .

Abstract 6585: OncoKB, MSK’s precision oncology knowledge base

Abstract OncoKB, Memorial Sloan Kettering Cancer Center’s (MSK) precision oncology knowledge base (www.oncokb.org), is an FDA-recognized* somatic variant database that contains information about the oncogenic effect and clinical implications of genomic alterations in cancer. Since its 2016 public release, OncoKB has grown to include annotation for >5,770 alterations in ~700 cancer-associated genes. OncoKB data is integrated into the cBioPortal for Cancer Genomics and used to annotate >12,000 MSK patient sequencing reports annually, encompassing both solid tumor and hematological malignancies. Users in academic, commercial and hospital settings outside MSK can programmatically access OncoKB data via its web API with an OncoKB license, which is free for academic research. To date, users from ~ 1400 institutions across >70 countries have licensed access to OncoKB annotations. The OncoKB Therapeutic (Tx) Levels of Evidence assign tumor-type specific clinical actionability to individual mutational events based on data supporting whether an alteration is predictive of response to matched targeted therapies. To date, OncoKB includes 44 Level 1 genes (included in the FDA drug label), 23 Level 2 genes (included in professional guidelines), 33 Level 3A genes (predictive of drug response in well-powered clinical studies), 27 Level 4 genes (predictive of drug response based on compelling biological evidence), and 11 R1/R2 resistance genes. In 2022, several major content additions were made to OncoKB based on key shifts in the precision oncology landscape. For example, OncoKB included 2 new tumor-agnostic FDA drug approvals, dabrafenib + trametinib and selpercatinib for BRAF V600E and RET fusion-positive solid tumors respectively (Level 1), capturing 5 tumor-agnostic FDA drug approvals to date. OncoKB promoted ERBB2 oncogenic mutations and FGFR1 fusions to Level 1 following their inclusion as patient eligibility criteria in FDA drug labels for trastuzumab deruxtecan (NSCLC) and pemigatinib (myeloid/lymphoid neoplasms) respectively. NCCN guidelines for uterine sarcoma and pancreatic cancer listed PARP-inhibition for BRCA-mutant disease, making them Level 2 in these indications. Lastly, previously considered undruggable targets, TP53 Y220C and KRAS G12D, were included in OncoKB based on compelling evidence demonstrating response to allele-targeting drugs, PC14586 and RMC-6263, respectively. In sum, 7 novel clinically actionable biomarkers (Levels 1-4) and 11 follow-on precision oncology therapies for existing leveled biomarkers were added to OncoKB in 2022. Current OncoKB efforts are focused on prioritized high-volume cancer gene curation for annotation of whole exome/genome data, annotation of germline alterations and development of a clinical trials matching system. *FDA recognition of OncoKB is partial and limited to the information clearly marked on www.oncokb.org. Citation Format: Sarah P. Suehnholz, Moriah Nissan, Hongxin Zhang, Ritika Kundra, Calvin Lu, Amanda Dhaneshwar, Nicole Fernandez, Stephanie Carrero, Maria E. Arcila, Marc Ladanyi, Michael F. Berger, Aijazuddin Syed, Rose Brannon, Ross Levine, Ahmet Dogan, Ezra Rosen, Alexander Drilon, David B. Solit, Nikolaus Schultz, Debyani Chakravarty. OncoKB, MSK’s precision oncology knowledge base. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6585.

Long-read sequencing identifies novel structural variations in colorectal cancer.

Structural variations (SVs) are a key type of cancer genomic alterations, contributing to oncogenesis and progression of many cancers, including colorectal cancer (CRC). However, SVs in CRC remain difficult to be reliably detected due to limited SV-detection capacity of the commonly used short-read sequencing. This study investigated the somatic SVs in 21 pairs of CRC samples by Nanopore whole-genome long-read sequencing. 5200 novel somatic SVs from 21 CRC patients (494 SVs / patient) were identified. A 4.9-Mbp long inversion that silences APC expression (confirmed by RNA-seq) and an 11.2-kbp inversion that structurally alters CFTR were identified. Two novel gene fusions that might functionally impact the oncogene RNF38 and the tumor-suppressor SMAD3 were detected. RNF38 fusion possesses metastasis-promoting ability confirmed by in vitro migration and invasion assay, and in vivo metastasis experiments. This work highlighted the various applications of long-read sequencing in cancer genome analysis, and shed new light on how somatic SVs structurally alter critical genes in CRC. The investigation on somatic SVs via nanopore sequencing revealed the potential of this genomic approach in facilitating precise diagnosis and personalized treatment of CRC.

Probing Clonal Hematopoiesis in Liquid Biopsy.

Increased use of liquid biopsy to pinpoint actionable genomic alterations in cancer has been accompanied by a rise in the incidental detection of clonal hematopoiesis. Its clinical significance remains unclear, however, as well as how best to risk-stratify patients for further evaluation and, if necessary, treatment.

A critical review of datasets and computational suites for improving cancer theranostics and biomarker discovery

Cancer has been constantly evolving and so is the research pertaining to cancer diagnosis and therapeutic regimens. Early detection and specific therapeutics are the key features of modern cancer therapy. These requirements can only be fulfilled with the integration of diverse high-throughput technologies. Integration of advanced omics methodology involving genomics, epigenomics, proteomics, and transcriptomics provide a clear understanding of multi-faceted cancer. In the past few years, tremendous high-throughput data have been generated from cancer genomics and epigenomic analyses, which on further methodological analyses can yield better biological insights. The major epigenetic alterations reported in cancer are DNA methylation levels, histone post-translational modifications, and epi-miRNA regulating the oncogenes and tumor suppressor genes. While the genomic analyses like gene expression profiling, cancer gene prediction, and genome annotation divulge the genetic alterations in oncogenes or tumor suppressor genes. Also, systems biology approach using biological networks is being extensively used to identify novel cancer biomarkers. Therefore, integration of these multi-dimensional approaches will help to identify potential diagnostic and therapeutic biomarkers. Here, we reviewed the critical databases and tools dedicated to various epigenomic and genomic alterations in cancer. The review further focuses on the multi-omics resources available for further validating the identified cancer biomarkers. We also highlighted the tools for cancer biomarker discovery using a systems biology approach utilizing genomic and epigenomic data. Biomarkers predicted using such integrative approaches are shown to be more clinically relevant.

1056P KRAS and LKB1 mutation conferring prognostic and predictive role on liquid biopsy in advanced NSCLC

Liquid biopsy (LB) is a feasible tool able to detect genomic alterations in cancer at baseline and also as a longitudinal monitoring to identify resistance mutations. In patients (pts) with mNSCLC, when tissue biopsy remains a difficult procedure, LB might be crucial for therapeutical options, especially in the immunotherapy (IO) and target therapy era. The aim of this bicentric study is to assess the prognostic value of LB in mNSCLC. Data from mNSCLC with any gene alteration/PD-L1 expression were collected at Istituto Nazionale Tumori of Milan and Policlinico Universitario of Naples. Liquid biopsy was performed by 73-gene Guardant360® CDx / 29-gene Archer® LiquidPlex™panels. Effects of circulating genomic alterations on Overall Survival (OS) (from 4-stage diagnosis to death/last FUP) were assessed using Cox proportional hazard model cell free. Kaplan-Meier curves were performed to assess OS between IO and non-IO treatments arms. Of 488 pts underwent LB, most were male (56.9%), former smoker (46.3%), with adenocarcinoma (73.6%) and PD-L1 > 1% (55.6%). 301/488 patients (62.6%) were treated with IO alone or in combination with chemotherapy, in first (47.0%) or second line (102 – 29.2%). In 133 (32.1%) cases, LB was performed at IO baseline, while in 101 (24.5%) cases at IO progression. Among the most relevant genes, STK11+/LKB1+ confers the worst OS (HR for OS 2.12 months, CI 95% 1.26 – 3.56; p = 0.005), regardless treatments. LKB1+/KRAS+ have a poorer OS than LKB1-/KRAS- (OS: 13 vs 24 m, HR 2.34 95% IC 1.19 – 4.61) and LKB1-/KRAS+ (OS: 13 vs 34 m HR 2.99 95% IC 1.36-6.54). When analyzing the effect of KRAS on IO and non-IO arms, KRAS-/IO have the best prognosis compared to KRAS+/non-IO which have the worst prognosis, while KRAS+/IO seems to have a similar prognosis to KRAS-/non-IO pts (HR 0.82 95% IC 0.43 – 1.58). Results reported on LB confirmed previous reports on tissue: STK11+ pts, have the worst prognosis regardless treatments. KRAS+ compare to STK11+/KRAS+ pts and STK11-/KRAS- pts seems to have the best prognosis. IO seems to play a relevant role on survival regardless KRAS status, in fact when using IO the negative prognostic effect of KRAS+ pts decreases and becomes similar to KRAS-/non-IO pts.

Analysis of genomic alterations in cancer associated human pancreatic stellate cells

Pancreatic stellate cells (PSCs) constitute important cells of the pancreatic microenvironment and their close interaction with cancer cells is important in pancreatic cancer. It is currently not known whether PSCs accumulate genetic alterations that contribute to tumor biology. Our aim was to analyze genetic alterations in cancer associated PSCs. PSC DNA was matched to DNA isolated from pancreatic cancer patients’ blood (n = 5) and analyzed by Next-Generation Sequencing (NGS). Bioinformatic analysis was performed using the GATK software and pathogenicity prediction scores. Sanger sequencing was carried out to verify specific genetic alterations in a larger panel of PSCs (n = 50). NGS and GATK analysis identified on average 26 single nucleotide variants in PSC DNA as compared to the matched blood DNA that could be visualized with the Integrative Genomics Viewer. The absence of PDAC driver mutations (KRAS, p53, p16/INK4a, SMAD4) confirmed that PSC isolations were not contaminated with cancer cells. After filtering the variants, using different pathogenicity scores, ten genes were identified (SERPINB2, CNTNAP4, DENND4B, DPP4, FGFBP2, MIGA2, POLE, SNRNP40, TOP2B, and ZDHHC18) in single samples and confirmed by Sanger sequencing. As a proof of concept, functional analysis using control and SERPINB2 knock-out fibroblasts revealed functional effects on growth, migration, and collagen contraction. In conclusion, PSC DNA exhibit a substantial amount of single nucleotide variants that might have functional effects potentially contributing to tumor aggressiveness.

AJS-3 Organ-specific and tumor-agnostic trials based on SCRUM-Japan MONSTAR-SCREEN

To implement precision oncology for patients with advanced solid tumors, we launched SCRUM-Japan MONSTAR-SCREEN, a nation-wide cancer genomic alterations screening project. In this project, patients with advanced solid tumors presenting to network institutions for clinical care were screened using a comprehensive tissue or liquid biopsy multi-omics analysis. After standard-of-care therapy, these patients were enrolled in suitably matched clinical trials.

Abstract PL03-02: Somatic mutations, germline risk and ancestry in lung adenocarcinoma

Abstract Like most cancer types, lung cancer is caused predominantly by somatic genome alterations. In lung adenocarcinoma, the most common histological type of lung cancer, these alterations are known to occur in multiple pathways including the p53 pathway, the receptor tyrosine kinase (RTK)/Ras/Raf/MAP kinase (MAPK) pathway and PI3 kinase pathway, the Rb1/cell cycle pathway, the Swi/Snf pathway, the Myc pathway, and the telomerase pathway, among others. Genome-wide association studies comparing polymorphisms in germline DNA from patients with lung cancer and from unaffected control subjects have led to the identification of multiple germline risk alleles for lung adenocarcinoma, including the HLA locus, the telomerase catalytic subunit gene locus, and, notably, the nicotinic acetylcholine receptor locus, where polymorphisms appear to modulate individual propensity for smoking. The components of inherited lung cancer risk, particularly in nonsmokers, are not fully understood, but there appear to be variations in lung adenocarcinoma mutations in distinct ancestry groups, which may be related to inherited factors. In particular, the frequency of somatic EGFR and KRAS mutations in lung cancer varies by ethnicity. Somatic EGFR mutation rates are higher in lung cancers from patients with East Asian ancestry and lower in lung cancers from patients with European or African ancestry. Somatic KRAS and STK11 mutation rates show the opposite pattern, higher in lung cancers from patients with European or African ancestry and lower in lung cancers from patients with East Asian ancestry. In patients from Latin America, somatic lung cancer EGFR mutation frequencies vary by country, with higher frequencies in Peru, intermediate frequencies in Mexico, Colombia, Costa Rica and Brazil, and lower frequencies in Argentina. To explore the relationship between the somatic genome in lung cancer and ethnicity related germline risk, we performed cancer gene panel sequencing of DNA from over 1,000 lung cancers from Mexico and Colombia, countries with significant population admixture. We developed methods to infer ancestry from the tumor DNA sequence based on coverage of single nucleotide polymorphisms. This study revealed associations between ancestry and somatic lung cancer genomic alterations, including tumor mutational burden, and specific driver mutations in EGFR, KRAS, and STK11. A local ancestry score was more strongly correlated with EGFR mutation frequency compared with global ancestry correlation, suggesting that germline genetics, rather than environmental exposure, could underlie these disparities. Our study suggests that the variation in EGFR and KRAS somatic mutation frequency in lung cancer is associated with genetic ancestry in patients from Latin America, and suggests further studies to identify germline alleles that underpin this association. If we find a germline locus or loci that could impact the development of lung cancers with EGFR and/or KRAS mutation, this might help in improving lung cancer prevention and screening for populations of Latin American origin and others. Furthermore, multiple studies now highlight the importance of EGFR mutation screening and EGFR-directed targeted therapy for lung cancer patients in Latin America and with origins in Latin America. Citation Format: Matthew L. Meyerson. Somatic mutations, germline risk and ancestry in lung adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr PL03-02.

Expanding clinical actionability in individual patient profiles with the Molecular Oncology Almanac.

3015 Background: The clinical care of oncology patients is routinely informed by tumor and inherited genetic profiles. This is accomplished by molecular pathologists synthesizing the growing body of clinical guidelines and scientific evidence that associates cancer genome alterations and therapeutic response, and applying that knowledge during case reviews. Many academic medical centers formalize this process in the form of molecular tumor boards. As the number of cases for review and literature continue to increase, there is opportunity to leverage clinical interpretation algorithms to computationally prioritize molecular features and both enhance and automate the sample contextualization process. Here, we present the Molecular Oncology Almanac (MOAlmanac) to enable the rapid assessment of tumor actionability. Methods: Molecular Oncology Almanac is an open source clinical interpretation algorithm and paired knowledge base for precision cancer medicine. It is used to rapidly characterize and identify genomic features related to therapeutic sensitivity and resistance and of prognostic relevance. This is performed by assessing not only individual genomic features (e.g. somatic variants, copy number alterations, germline variants, and fusions) but also interactions between these events as well as secondary features such as mutational burden, mutational signatures, MSI status, and aneuploidy. MOAlmanac summarizes all clinically relevant findings into a web-based actionability report. The underlying knowledge base can be accessed through our API endpoints and web browser, and entries may be recommended through either Github or our browser extension. In addition, we developed a cloud-based web portal on top of the Terra framework to increase accessibility. Results: A total of 32,108 samples from 30,607 patients across 66 cancer types received targeted sequencing to characterize somatic variants, copy number alterations, and fusions from PROFILE’s Oncopanel and were evaluated with MOAlmanac. Based on Oncopanel’s tier 1 and tier 2 criteria for clinical actionability, we observed that 8,285 samples (26%, 0 - 69% by cancer type) of patients harbored at least one alteration suggesting therapeutic sensitivity based on FDA approvals or clinical guidelines. Actionability increases to 18,117 samples (56%, 0 - 85% by cancer type) when considering an expanded set of evidence to include relationships captured from clinical trials, clinical, preclinical, and inferential evidence; consequently providing at least one therapeutic hypothesis to otherwise variant-negative patients. Conclusions: Clinical actionability of molecular tumor data was increased in individual patients by expanding the set of evidence considered. Source code and a web portal for this project are available at moalmanac.org .