Genomic Biomarkers Research Articles

Molecular risk factors for locoregional recurrence in resected non-small cell lung cancer.

Locoregional recurrence is of high risk and is associated with a poor prognosis in terms of OS for non-small cell lung cancer (NSCLC). Local control is essential for radical cure of NSCLC. Previous studies have investigated the clinicopathological risk factors for locoregional recurrence, but the genomic biomarkers associated with locoregional recurrence have been inadequately studied. A total of 118 patients who underwent tumor resection with mutation-detected tumor specimens were included. Tumor samples at surgery and pretreatment/postoperative blood samples were collected for mutational profiling. Among 48 patients with disease recurrence, 46% developed locoregional recurrence (LR) and 75% developed distant metastasis (DM). The 3-year actuarial risk of LR and DM was 25% and 43%, respectively. The first sites of failure were locoregional only (29%), locoregional and distant (10%), and distant only (61%). Patients with LR showed significantly higher ctDNA level than those with only DM at the time of initial recurrence. On multivariate analysis of baseline risk factors, the presence of allele frequency heterogeneity and baseline ctDNA shedding were found to be independently associated with a higher risk of LR. Patients with disruptive TP53 mutations had significantly lower LR-free survival as compared to patients with wild-type TP53 or nondisruptive mutations. EGFR mutations showed a favorable prognostic value for LR and is not induced by EGFR tyrosine kinase inhibitor therapy. Both disruptive TP53 mutation and EGFR mutation remained the significant prognostic factor after adjustment for histological type, pathologic nodal stage and adjuvant therapy. Nearly half of disease recurrences after surgery for NSCC involved locoregional sites. We identified genomic biomarkers from baseline tumor and ctDNA samples which showed promising prognostic value for LR only. This can help identify patients who had a higher risk of locoregional recurrence regardless of the risk of distant metastasis.

Standing in the canine precision medicine knowledge gap: Improving annotation of canine cancer genomic biomarkers through systematic comparative analysis of human cancer mutations in COSMIC.

The accrual of cancer mutation data and related functional and clinical associations have revolutionised human oncology, enabling the advancement of precision medicine and biomarker-guided clinical management. The catalogue of cancer mutations is also growing in canine cancers. However, without direct high-powered functional data in dogs, it remains challenging to interpret and utilise them in research and clinical settings. It is well-recognised that canine and human cancers share genetic, molecular and phenotypic similarities. Therefore, leveraging the massive wealth of human mutation data may help advance canine oncology. Here, we present a structured analysis of sequence conservation and conversion of human mutations to the canine genome through a 'caninisation' process. We applied this analysis to COSMIC, the Catalogue of Somatic Mutations in Cancer, the most prominent human cancer mutation database. For the project's initial phase, we focused on the subset of the COSMIC data corresponding to Cancer Gene Census (CGC) genes. A total of 670 canine orthologs were found for 721 CGC genes. In these genes, 365 K unique mutations across 160 tumour types were converted successfully to canine coordinates. We identified shared putative cancer-driving mutations, including pathogenic and hotspot mutations and mutations bearing similar biomarker associations with diagnostic, prognostic and therapeutic utility. Thus, this structured caninisation of human cancer mutations facilitates the interpretation and annotation of canine mutations and helps bridge the knowledge gap to enable canine precision medicine.

Predictive genomic biomarkers of therapeutic effects in renal cell carcinoma.

In recent years, there have been great improvements in the therapy of renal cell carcinoma. Nevertheless, the therapeutic effect varies significantly from person to person. To discern the effective treatment for different populations, predictive molecular biomarkers in response to target, immunological, and combined therapies are widely studied. This review summarized those studies from three perspectives (SNPs, mutation, and expression level) and listed the relationship between biomarkers and therapeutic effect, highlighting the great potential of predictive molecular biomarkers in metastatic RCC therapy. However, due to a series of reasons, most of these findings require further validation.

Expression profile of HERVs and inflammatory mediators detected in nasal mucosa as a predictive biomarker of COVID-19 severity.

Our research group and others demonstrated the implication of the human endogenous retroviruses (HERVs) in SARS-CoV-2 infection and their association with disease progression, suggesting HERVs as contributing factors in COVID-19 immunopathology. To identify early predictive biomarkers of the COVID-19 severity, we analyzed the expression of HERVs and inflammatory mediators in SARS-CoV-2-positive and -negative nasopharyngeal/oropharyngeal swabs with respect to biochemical parameters and clinical outcome. Residuals of swab samples (20 SARS-CoV-2-negative and 43 SARS-CoV-2-positive) were collected during the first wave of the pandemic and expression levels of HERVs and inflammatory mediators were analyzed by qRT-Real time PCR. The results obtained show that infection with SARS-CoV-2 resulted in a general increase in the expression of HERVs and mediators of the immune response. In particular, SARS-CoV-2 infection is associated with increased expression of HERV-K and HERV-W, IL-1β, IL-6, IL-17, TNF-α, MCP-1, INF-γ, TLR-3, and TLR-7, while lower levels of IL-10, IFN-α, IFN-β, and TLR-4 were found in individuals who underwent hospitalization. Moreover, higher expression of HERV-W, IL-1β, IL-6, IFN-α, and IFN-β reflected the respiratory outcome of patients during hospitalization. Interestingly, a machine learning model was able to classify hospitalized vs not hospitalized patients with good accuracy based on the expression levels of HERV-K, HERV-W, IL-6, TNF-a, TLR-3, TLR-7, and the N gene of SARS-CoV-2. These latest biomarkers also correlated with parameters of coagulation and inflammation. Overall, the present results suggest HERVs as contributing elements in COVID-19 and early genomic biomarkers to predict COVID-19 severity and disease outcome.

Development and Validation of Blood-Based Predictive Biomarkers for Response to PD-1/PD-L1 Checkpoint Inhibitors: Evidence of a Universal Systemic Core of 3D Immunogenetic Profiling across Multiple Oncological Indications.

Unprecedented advantages in cancer treatment with immune checkpoint inhibitors (ICIs) remain limited to only a subset of patients. Systemic analyses of the regulatory 3D genome architecture linked to individual epigenetic and immunogenetic controls associated with tumour immune evasion mechanisms and immune checkpoint pathways reveal a highly prevalent molecular profile predictive of response to PD-1/PD-L1 ICIs. A clinical blood test based on a set of eight (8) 3D genomic biomarkers has been developed and validated on the basis of an observational trial to predict response to ICI therapy. The predictive eight biomarker set is derived from prospective observational clinical trials, representing 280 treatments with Pembrolizumab, Atezolizumab, Durvalumab, Nivolumab, and Avelumab in a broad range of indications: melanoma, lung, hepatocellular, renal, breast, bladder, colon, head and neck, bone, brain, lymphoma, prostate, vulvar, and cervical cancers. The 3D genomic eight biomarker panel for response to immune checkpoint therapy achieved a high accuracy of 85%, sensitivity of 93%, and specificity of 82%. This study demonstrates that a 3D genomic approach can be used to develop a predictive clinical assay for response to PD-1/PD-L1 checkpoint inhibition in cancer patients.

The prospect of genomic, transcriptomic, epigenetic and metabolomic biomarkers for the personalized prevention of type 2 diabetes and cardiovascular diseases.

Cardiometabolic diseases, such as type 2 diabetes mellitus (DM) and cardiovascular disease (CVD), are a great health concern. The strategies aimed to increase awareness and prevention, in conjunction with timely diagnosis and optimal management of these conditions, represent the main lines of action to improve life expectancy and quality. In recent years, the introduction of innovative therapies for the treatment of DM and CVD has provided new hope for high-risk patients. Yet, the implementation of preventive measures in achieving cardiometabolic health is far from successful and requires further improvement. The development of cardiometabolic disorders is a complex, multifactorial process involving several metabolic pathways as well as genetic and environmental factors. Decreasing cumulative exposure during the entire life course and timely recognition and targeting of potential risk-enhancing factors could pave the way toward more successful prevention of cardiometabolic disorders. Nowadays, in the era of "omics" technologies, it is possible to identify novel biomarkers and therapeutic targets, which offers the possibility to apply an individualized approach for each patient. This review will discuss potential applications of genomic, transcriptomic, epigenetic and metabolomic biomarkers for the personalized prevention of cardiometabolic diseases.

Pain sensation and gut microbiota profiles in older adults with heart failure.

Patients with heart failure (HF) experience severe pain and may have altered pain sensation; however, the underlying mechanisms of these symptoms are not yet fully understood. Identifying pain sensation and genomic biomarkers of pain in older adults with HF is a critical step toward developing personalized interventions to improve pain management and outcomes. This study aimed to investigate the differences in pain sensation, gut microbiota, self-reported pain, and symptoms in older adults with and without HF. Twenty older adults with HF and age-matched healthy controls (HCs) were recruited in the Northeastern United States. Quantitative sensory testing and conditioned pain modulation were performed on the nondominant upper arm to detect the mechanical, thermal, and pressure pain thresholds and pain modulations. Stool samples were collected, and the 16S rRNA V4 gene region of stool samples was sequenced and processed using the Mothur 1.42.3 pipeline. Self-reported pain and symptoms were measured by the Brief Pain Inventory and the NIH Patient-reported Outcomes Measurement Information System. The associations between pain sensation, gut microbiota α-diversity indices, and pain and symptoms were explored using the Spearman correlations. The HF and HC subjects' mean ages were 73.50 (SD = 8.33) and 67.10 (SD = 7.64), respectively. The HF subjects reported significantly higher pain intensity and interference, sleep disturbance, fatigue, anxiety, and depression than the HCs. The HF subjects also had a significantly lower level of physical function and participation in social roles and activities. Compared with the HCs, the HF subjects had significantly altered conditioned pain modulation heat effect and gut microbiota compositions and predicted metabolic functions. The Statistical Analysis Of Metagenomic Profiles indicated that the HF subjects had a significantly decreased cardiac muscle contraction pathway compared with the HCs. The correlation analysis showed that the quantitative sensory testing profiles and gut microbiota diversity index were significantly associated with pain and symptoms in older adults with HF. Older adults with HF had more severe self-reported pain and symptoms, altered pain sensation, and different gut microbiota composition and function compared with age-matched HCs. Pain sensation and gut microbiota may contribute to pain and symptoms in older adults with HF and could serve as biomarkers of pain and symptoms of HF. Further research with a larger sample size is warranted to confirm these findings.

Clinical predominance of whole-exome sequencing to evaluate microsatellite instability status.

The microsatellite instability (MSI)/mismatch repair (MMR) status is one of the critical genomic biomarkers for predicting patient response to immune checkpoint inhibitors (ICIs). In this study, we aimed to investigate the concordance among the MSIsensor score obtained from whole-exome sequencing (WES), which could be a futuristic clinical cancer sequencing method, using only tumor tissues, MSI-PCR results, and immunohistochemistry (IHC) results to analyze various solid cancer types. We first endeavored to set the cut-off value of MSIsensor to determine functional deficient mismatch repair (f-dMMR) status. The MSI status of 1054 patients analyzed using WES was evaluated using MSIsensor. In addition, 87 of these patients were further analyzed using MSI-PCR and MMR IHC to calculate the sensitivity and specificity of the MSIsensor cut-off score. Our results showed that score 12.5 was an adequate cut-off score equivalent to PCR-confirmed MSS/MSI-low and MSI-high statuses, with sensitivity, specificity, and area under the curve values of 95.2%, 100%, and 0.998, respectively. Moreover, we identified false-positive cases of tumors with high mutational burden with an MSIsensor score <12.5, and optional IHC examination could rescue these cases. In conclusion, the MSIsensor score obtained using WES with tumor tissue showed a high clinical validity, with a cut-off value of 12.5 for f-dMMR detection, in combination with optional IHC analysis for MMR. Our novel algorithm will provide insights into the development of ICIs for cancer treatment, particularly when WES becomes a more common cancer genomic test in the near future.

Triplet Therapy in Metastatic Castrate Sensitive Prostate Cancer (mCSPC)-A Potential New Standard of Care.

The treatment paradigm for metastatic castrate-sensitive prostate cancer (mCSPC) has evolved rapidly in the past decade with the approval of several life-prolonging therapies including docetaxel chemotherapy and multiple androgen receptor pathway inhibitors (ARPI) in combination with androgen deprivation therapy (ADT). Recently reported phase-three trials have demonstrated a survival benefit of upfront triplet therapy with ADT, docetaxel plus either abiraterone acetate or darolutamide when compared to ADT plus docetaxel alone. However, multiple questions including the incremental benefit of docetaxel to a combination of ADT and ARPI, the timing of ARPI, optimal patient selection for triplet therapy and clinical and genomic biomarkers still remain to be answered. Moreover, real-world data suggest suboptimal treatment intensification with many patients treated with ADT alone highlighting challenges in implementation. In this article, we review the phase-three data associated with triplet therapy in mCSPC. We also discuss the knowledge gaps that exist despite the completion of these studies and how ongoing studies are likely to change the paradigm in the near future. Finally, we provide a simple algorithm based on current data that clinicians can use in daily practice to select patients for appropriate treatment strategies.

Systematic review of the role of genomic salivary biomarkers in the early detection of oral cancer

Cancer is a large group of diseases that can start in almost any organ or tissue of the body when abnormal cells grow uncontrollably, and metastasize to any other part of the body. India reports approximately one-fourth of global incidences of oral cancer annually, that is, around 77,000 new cases and 52,000 deaths. While cancer is the second leading cause of death worldwide, oral squamous cell carcinoma (OSCC) is one of the most prevalent cancers with a global incidence of more than 350,000 new cases and 177,000 deaths every year. Since the average 5-year survival rate of oral cancer on early diagnosis is 77.3% in stages I and II along with a better prognosis, but only 32.2% in stages III and IV, early detection of oral cancer is pertinent for prompt treatment of the problem at its grassroot level to decrease the subsequent morbidity and mortality associated with the disease. This article has been written as a compilation of the various genomic salivary biomarkers that have been detected in the saliva of cancer patients to inculcate a better understanding of these biomarkers and the role they play in the early detection of oral cancer. This will provide adequate knowledge to general and oral surgeons, as well as cancer biologists about the salivary diagnostic markers which will act as an adjunct to the traditional methods of cancer detection. The articles were selected from PubMed/Medline and Google Scholar. The articles with higher academic relevance were selected.

Abstract CT118: A phase I/II trial of a CXCR1/2 inhibitor in combination with anti-PD-1 for circulating tumor DNA (ctDNA) positive &amp; refractoryRAS-mutated microsatellite stable (MSS) colorectal cancer

Abstract Background: Preclinical CRC models reveal KRAS mutations activate the CXCR2 axis promoting an immunosuppressive tumor microenvironment (TME). This occurs via KRAS repression of interferon regulatory factor 2 (IRF2) resulting in upregulation of CXCL3 chemokines, which bind CXCR2 and recruit myeloid-derived suppressor cells (MDSC; Liao et al, Cancer Cell 2019). MDSCs also accelerate metastases by ‘priming’ the premetastatic niche via promoting egress of tumors cells into the circulation, inhibiting killing by immune cells and promoting extravasation into the tissues (Veglia et al. Nature 2021). SX-682 is a novel oral small-molecule inhibitor of CXCR1/2 chemokine receptors involved in MDSC-recruitment to TME. This proof-of-concept study investigates whether a CXCR1/2 antagonist in combination with anti-PD-1 therapy can overcome de novo immunotherapy resistance in MSS RAS mutated mCRC and eradicate micrometastatic disease in ctDNA positive CRC post definitive therapy. Methods: STOPTRAFFIC-1 is a phase I/II, open-label, dose-escalation/dose expansion study of SX-682 plus nivolumab for patients (pts) with RAS mutated MSS mCRC or ctDNA positive CRC. Key eligibility criteria - Arm A: pts with MSS mCRC with progression or intolerance to 2 prior lines of therapy, ECOG 0/1; Arm B: ctDNA positive post completion of definitive therapy (adjuvant chemotherapy for stage III or metastasectomy for stage IV CRC). Pts will receive SX-682 (5 dose levels: 25 mg, 50 mg, 100mg, 200mg, or 400 mg PO twice daily) in an 8-week cycle with intravenous nivolumab (480 mg) on days 1 and 29. Adverse events per CTCAE v5.0. RECIST assessments every 8 weeks. In dose escalation, pts enter a 3-week monotherapy safety run-in of SX-682 followed by 3-week combination with nivolumab for a six-week dose-limiting toxicity (DLT) period. Cohorts 1-4 have been completed without DLT. Enrollment to Cohort 5 is completed with expansion arms to open February 2023. Dose expansion is a Simon's optimal two-stage design for Arm A. Efficacy will be assessed in the first 15 pts with a requirement of 2 responses in order to enroll 14 additional pts (N=29). Pre- and on-treatment tissue biopsies will be collected. Arm B will enroll 15 pts with positive ctDNA post definitive therapy. Pts will be screened with CLIA certified ctDNA test for minimal residual disease (MRD) and if positive, enrolled for treatment for up to 6 months (m). Pts will undergo radiographic evaluation at 3 and 6m and then every 3-6m for at least 3 years. The primary objectives are to determine safety profile, recommended phase 2 dose, clinical activity &amp; 6m ctDNA clearance rate in CRC pts with MRD following 6m of SX-682 + Nivolumab on Arm B. Translational analyses include correlations of clinical outcomes with genomic and immune biomarkers from paired tissue and plasma samples. Clinical trial information: NCT04599140. Citation Format: Benny Johnson, Cara Haymaker, Van K. Morris, Arvind Dasari, Victoria Serpas Higbie, John Paul Shen, Christine Parseghian, Maria Pia Morelli, Ryan Huey, Michael S. Lee, Jason Willis, Kanwal P. Raghav, Ying Yuan, John Zebala, Ronald A. DePinho, Scott Kopetz, Michael Overman. A phase I/II trial of a CXCR1/2 inhibitor in combination with anti-PD-1 for circulating tumor DNA (ctDNA) positive &amp; refractoryRAS-mutated microsatellite stable (MSS) colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr CT118.

Neuroendocrine Tumors: Genomics and Molecular Biomarkers with a Focus on Metastatic Disease.

Neuroendocrine tumors (NETs) are considered rare tumors that originate from specialized endocrine cells. Patients often present with metastatic disease at the time of diagnosis, which negatively impacts their quality of life and overall survival. An understanding of the genetic mutations that drive these tumors and the biomarkers used to detect new NET cases is important to identify patients at an earlier disease stage. Elevations in CgA, synaptophysin, and 5-HIAA are most commonly used to identify NETs and assess prognosis; however, new advances in whole genome sequencing and multigenomic blood assays have allowed for a greater understanding of the drivers of NETs and more sensitive and specific tests to diagnose tumors and assess disease response. Treating NET liver metastases is important in managing hormonal or carcinoid symptoms and is imperative to improve patient survival. Treatment for liver-dominant disease is varied; delineating biomarkers that may predict response will allow for better patient stratification.

Integrated multiomics analyses unveil the implication of a costimulatory molecule score on tumor aggressiveness and immune evasion in breast cancer: A large-scale study through over 8,000 patients

BackgroundAlthough immunotherapy has revolutionised cancer management, reliable genomic biomarkers for identifying eligible patient subpopulations are lacking. Costimulatory molecules play a crucial role in mounting anti-tumour responses, and clinical trials targeting these novel biomarkers are underway. However, whether these molecules can determine tumour aggressiveness and the risk of tumour evasion in breast cancer (BC) remains largely unknown. MethodsThe whole-tissue transcriptomic data of 8236 patients with BC from 15 independent cohorts were extracted. An integrated scoring system named ‘costimulatory molecule score’ (CMS) was constructed and sufficient validated using least absolute shrinkage and selection operator regression (1000 iterations) and the random survival forest algorithm (1000 trees). The correlation among CMSs, cancer genotypes and clinicopathological characteristics was examined. Extensive multiomics and immunogenomic analyses were performed to investigate and verify the association among CMSs, enriched pathways, potential intrinsic and extrinsic immune escape mechanisms, immunotherapy response and therapeutic options. ResultsThe predictive role of CMS model that relies on expression pattern of merely 5 costimulatory genes for prognosis is almost universally applicable to BC patients in a platform-independent manner. Through internal and external in silico validation, high CMS was characterized by favorable genotypes but decreased tumor immunogenicity, activation of stroma, immune-suppressive states and potential immunotherapeutic resistance. Similar results were observed in a real-world immunotherapy cohort and Pan-Cancer analysis. ConclusionThis comprehensive characterization indicates CMS model may be complemented for predicting tumor aggressiveness and immune evasion in BC patients, underlining the future clinical potential for further exploration of resistance mechanisms and optimization of immunotherapeutic strategies.

Abstract 2089: Vanishing deviance problem in high-dimensional penalized Cox regression

Abstract Penalized regression models, such as LASSO and elastic net, have been well-established for high-dimensional variable sections. For the analysis of censored survival outcomes, the penalized Cox regression model has been widely used. The parameter tuning in the penalized regression is often implemented based on the cross-validation (CV) via the “one standard error rule” (1se rule), resulting in a more parsimonious model. However, in a high-dimensional Cox regression model, a common observation is that the CV plot for tuning parameters against partial-likelihood deviance is often not U-shaped but L-shaped. In this case, the model selection will fail with either the “1se” or the“min” rule. We observed that this phenomenon is quite universal in the setting of high-dimensional prognostic biomarker selection, in which the standard CV steps often result in no or very few features included in the final model. We refer to this phenomenon as the “vanishing deviance” (VD) problem. In this study, we investigated this problem in more depth and demonstrated the issue and potential solution using real data from pan-cancer analysis of prognostic lncRNA biomarkers. To discover the cause behind the VD problem, we conducted an extensive set of simulations by varying sample sizes, feature dimensions, censoring rates, number of true biomarkers, and significance levels of true signals.Our results indicated that the main cause of the VD problem can be related to the limited sample size in the cancer omics dataset and a large number of true (or highly associated) biomarkers or signals underlying. To this end, we propose computational solutions that can alleviate the problem and we implemented them in the R package called CoxHive. We verified the performance of our solution based on both simulation studies and the analyses of the pan-cancer gene expression data. This software tool will greatly facilitate biomarker selection (including genomic and imaging biomarkers) in the high-dimensional setting. Citation Format: Sijie Yao, Tingyi Li, Biwei Cao, Xuefeng Wang. Vanishing deviance problem in high-dimensional penalized Cox regression [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 2089.

Abstract 2224: Applying optical genome mapping to detect genomic biomarkers and use for residual disease monitoring in hematologic malignancies

Abstract Disease monitoring is important to detect cancer relapse, often as a result of a treatment-surviving cancer cell population. Detection of relapse is critical to determine the intensity and length of treatments and to predict the outcome of those treatments. Currently, karyotyping, fluorescent in situ hybridization (FISH), flow cytometry, PCR, and next-generation sequencing (NGS) are often used for this application. PCR is sensitive and highly effective, but as a targeted approach, it requires the identification of an appropriate biomarker. Karyotyping and FISH are used to follow structural variants, especially those detected at diagnosis and known to be drivers of carcinogenesis; however, karyotype has low sensitivity (~5-10% variant allele frequency (VAF)) and FISH is only targeted.We describe a novel workflow to find structural variants (SVs) using optical genome mapping (OGM) and to use those SVs as biomarkers for disease monitoring assessment. The initial SV profile from a cancer sample can be obtained by running the standard somatic workflow for OGM: 1.5 Tbp of high molecular genomic DNA is collected (without any amplification/selection), and molecules that can capture SV breakpoints are locally assembled into genome maps. These locally assembled genome maps are used to make high-confidence SV calls at least 5 kbp in size. Then, presumptive somatic variants are revealed by further comparison against an OGM control sample SV database (included in Bionano Access/Solve software). Subsequently, to detect residual cancer cells post-treatment, an ultra-deep coverage of approximately 5 Tbp of DNA can be collected, and these molecules are directly aligned to the genome maps in the initial cancer sample. This direct alignment approach is fast and sensitive in identifying remnants of pretreatment originator cells. We are currently applying this workflow to recover known leukemia-associated inter-chromosomal translocations, and our preliminary results indicate a sensitivity of detecting calls at a minimum of 0.5% VAF. Continual investigation on limit of detection is ongoing, but with the improvement on throughput and algorithms, we envision that this workflow to be essential in discovering low level clonal cancerous DNA. Citation Format: Alex Chitsazan, Andy Pang, Alex Hastie. Applying optical genome mapping to detect genomic biomarkers and use for residual disease monitoring in hematologic malignancies [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 2224.

Copy Number Variation in Inflammatory Breast Cancer.

Identification of a unique genomic biomarker in de novo inflammatory breast cancer (IBC) may provide an insight into the biology of this aggressive disease. The goal of our study was to elucidate biomarkers associated with IBC. We examined breast biopsies collected from Dana-Farber Cancer Institute patients with IBC prior to initiating preoperative systemic treatment (30 samples were examined, of which 14 were eligible). Patients without available biopsies (n = 1), with insufficient tumor epithelial cells (n = 10), or insufficient DNA yield (n = 5) were excluded from the analysis. Molecular subtype and tumor grade were abstracted from a medical records' review. Ten IBC tumors were estrogen-receptor-positive (ER+) and human epidermal growth factor receptor 2 (HER2)-negative (n = 10 out of 14). Sufficient RNA and DNA were simultaneously extracted from 14 biopsy specimens using the Qiagen AllPrep Kit. RNA was amplified using the Sensation kit and profiled using the Affymetrix Human Transcriptome Array 2.0. DNA was profiled for genome-wide copy number variation (CNV) using the Affymetrix OncoScan Array and analyzed using the Nexus Chromosome Analysis Suite. Among the 14 eligible samples, we first confirmed biological concordance and quality control metrics using replicates and gene expression data. Second, we examined CNVs and gene expression change by IBC subtype. We identified significant CNVs in IBC patients after adjusting for multiple comparisons. Next, to assess whether the CNVs were unique to IBC, we compared the IBC CNV data to fresh-frozen non-IBC CNV data from The Cancer Genome Atlas (n = 388). On chromosome 7p11.2, we identified significant CN gain located at position 58,019,983-58,025,423 in 8 ER+ IBC samples compared to 338 non-IBC ER+ samples (region length: 5440 bp gain and 69,039 bp, False Discovery Rate (FDR) p-value = 3.12 × 10-10) and at position 57,950,944-58,025,423 in 3 TN-IBC samples compared to 50 non-IBC TN samples (74,479 base pair, gain, FDR p-value = 4.27 × 10-5; near the EGFR gene). We also observed significant CN loss on chromosome 21, located at position 9,648,315-9,764,385 (p-value = 4.27 × 10-5). Secondarily, differential gene expression in IBC patients with 7p11.2 CN gain compared to SUM149 were explored after FDR correction for multiple testing (p-value = 0.0016), but the results should be interpreted with caution due to the small sample size. Finally, the data presented are hypothesis-generating. Validation of CNVs that contribute to the unique presentation and biological features associated with IBC in larger datasets may lead to the optimization of treatment strategies.

MP17-04 IMPACT OF TISSUE-BASED GENOMIC TESTING ON PAYMENTS FOR PROSTATE CANCER CARE

You have accessJournal of UrologyCME1 Apr 2023MP17-04 IMPACT OF TISSUE-BASED GENOMIC TESTING ON PAYMENTS FOR PROSTATE CANCER CARE Benjamin Croll, Dattatraya Patil, Sagar Patel, and Christopher Filson Benjamin CrollBenjamin Croll More articles by this author , Dattatraya PatilDattatraya Patil More articles by this author , Sagar PatelSagar Patel More articles by this author , and Christopher FilsonChristopher Filson More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003237.04AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Tissue-based genomic biomarkers have been approved for use in risk-stratification of prostate cancer for more than a decade. Prior cost analyses relied on simulation modeling of artificial cohorts, and there has been limited research on real-world expenditures. We assessed 12-month post-biopsy healthcare payments to compare payer expenditures for prostate cancer patients who did and did not receive post-biopsy tissue-based genomic testing. METHODS: We used IBM MarketScan Commercial Claims and Medicare Supplemental data to identify newly-diagnosed patients (2018–2019). Inflation-adjusted total healthcare payments were calculated in the 12-month period following diagnostic biopsy. Outliers with the top and bottom 2.5% percentile of total payments were excluded. Multivariable linear regression was conducted to estimate the effect of receiving genomic testing (Oncotype DX, Prolaris, and Decipher) on payments, after controlling for treatment modality, insurance status, and other demographic information. We stratified our analysis based on treatment received. RESULTS: We identified 10,859 patients in our cohort (9,242 privately-insured; 1,617 Medicare eligible). Among this group, 24% received radiation therapy (RT), 44% had radical prostatectomy (RP), and 33% had no identified treatment (AS/WW/NT). Genomic testing was more common in 2019 than 2018 (6.9% vs. 3.5%, p<.001) and was more common in the AS/WW/NT group (8.3%) than those treated with RT (3.4%) or RP (3.9%), p<.001. Median payments for each genomic test ranged from $2,156-3,873. Prediction modeling based on multivariable analysis demonstrated that genomic testing is associated with payment differences ranging from -$119 to +$494 in individual treatment groups (Figure 1). CONCLUSIONS: Use of tissue-based genomic testing is associated with significant expense. Despite this expense, their use was associated with similar total payments across treatment groups, with the greatest savings ($119) in Medicare patients receiving RT and the greatest expense in Medicare patients undergoing RP ($494). Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e213 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Benjamin Croll More articles by this author Dattatraya Patil More articles by this author Sagar Patel More articles by this author Christopher Filson More articles by this author Expand All Advertisement PDF downloadLoading ...

MP19-19 PRIORITIZED RESEARCH QUESTIONS ON THE USE OF ACTIVE SURVEILLANCE FOR THE MANAGEMENT OF PROSTATE CANCER: RESULTS FROM PCASRI CONFERENCE

MP19-19 PRIORITIZED RESEARCH QUESTIONS ON THE USE OF ACTIVE SURVEILLANCE FOR THE MANAGEMENT OF PROSTATE CANCER: RESULTS FROM PCASRI CONFERENCE

Expert Consensus Recommendations on Biomarker Testing in Metastatic and Nonmetastatic NSCLC in Asia.

Most published guidelines for genomic biomarker testing in NSCLC reflect the disease epidemiology and treatments readily available in Europe and North America. Nevertheless, 60% of annual global NSCLC cases occur in Asia, where patient characteristics, tumor molecular profiles, and treatments vary greatly from the Western world. For example, mutations in the EGFR occur at a higher prevalence in Asia than in other world regions. Although medical associations such as the International Association for the Study of Lung Cancer, European Society for Medical Oncology, and American Society of Clinical Oncology have described principles for tumor genomic biomarker testing in NSCLC, there is a need for recommendations specific for Asia. This report provides consensus recommendations for NSCLC biomarker testing from Asian lung cancer experts for clinicians working in Asia to improve patient care. Biomarker testing approaches for actionable genetic alterations inEGFR,ALK,ROS1, and others are discussed. These recommendations are divided into nonmetastatic and metastatic forms of adenocarcinoma and squamous cell carcinoma. Owing to the higher prevalence of EGFR mutations in Asia, the experts emphasized the need for EGFR testing to include not just common mutations (exon 19 deletions and L858R substitutions) but also other uncommon EGFR mutations. In addition to the assessment of biomarkers in the tumor tissue, the role of assessing tumor biomarkers by liquid biopsy is discussed. This consensus provides practical recommendations for biomarker testing in nonmetastatic and metastatic Asian NSCLC patients.

Interview: Timothy Clinton

Interview: Timothy Clinton