Detection Of Recurrent Cancer Research Articles

72301 - Breast cancer recurrence detection in relation to surveillance - applications on personalized follow-up

72301 - Breast cancer recurrence detection in relation to surveillance - applications on personalized follow-up

18F-FDG PET/CT- and MRI-Based Locally Advanced Cervical Cancer Early-Response Assessment after Concurrent Chemo- and Radiotherapy-Impact on Patient Outcomes and Survival Prediction.

With one third of patients with locally advanced cervical cancer (LACC) expected to develop cancer recurrence in the first two years after therapy, accurate assessment of the response and timely detection of cancer recurrence after concurrent chemo- and radiotherapy (CCRT) treatment is of great importance. Although there is neither definite consensus about the preferred imaging modality, nor the time interval until the first diagnostic examination after CCRT, the National Comprehensive Cancer Network (NCCN) recommends the use of MRI and 18F-FDG PET/CT as a post-treatment LACC response-assessment imaging tools. In this study, we tried to appraise the early therapy response in LACC patients by both 18F-FDG PET/CT and MRI in regard to the follow-up imaging results and their mutual interrelationship, and to ascertain if the post-treatment 18F-FDG PET/CT and MRI results were related to the progression-free and overall survival rate in women with LACC after CCRT. We also aimed to estimate the early and follow-up diagnostic imaging impact on further therapy management. Based on our results, we concluded that 18F-FDG PET/CT did surpass MRI in the early assessment of therapeutic response in LACC patients after CCRT. Both modalities provided information that may serve as predictive biomarkers of outcome and LACC patients' survival.

Decoding the Dynamics of Circulating Tumor DNA in Liquid Biopsies.

Circulating tumor DNA (ctDNA), a fragment of tumor DNA found in the bloodstream, has emerged as a revolutionary tool in cancer management. This review delves into the biology of ctDNA, examining release mechanisms, including necrosis, apoptosis, and active secretion, all of which offer information about the state and nature of the tumor. Comprehensive DNA profiling has been enabled by methods such as whole genome sequencing and methylation analysis. The low abundance of the ctDNA fraction makes alternative techniques, such as digital PCR and targeted next-generation exome sequencing, more valuable and accurate for mutation profiling and detection. There are numerous clinical applications for ctDNA analysis, including non-invasive liquid biopsies for minimal residual disease monitoring to detect cancer recurrence, personalized medicine by mutation profiling for targeted therapy identification, early cancer detection, and real-time evaluation of therapeutic response. Integrating ctDNA analysis into routine clinical practice creates promising avenues for successful and personalized cancer care, from diagnosis to treatment and follow-up.

Head-to-head comparison of [68Ga]Ga-FAPI-04 PET and [18F]FDG PET in the detection of cancer recurrence: a systematic review and meta-analysis.

The comparative diagnostic performance of [68Ga]Ga-fibroblast activation protein inhibitors-04 {[68Ga]Ga-FAPI-04} positron emission tomography (PET) and fluorodeoxyglucose F 18 {[18F]FDG} PET in identifying cancer recurrence remains uncertain. The purpose of our study was to compare the diagnostic performance of [68Ga]Ga-FAPI-04 PET and [18F]FDG PET imaging in cancer recurrence. Up until March 1, 2024, we searched PubMed, Embase, and Web of Science for pertinent papers. Studies examining the diagnostic utility of [68Ga]Ga-FAPI-04 PET and [18F]FDG PET for cancer recurrence were included. Using a bivariate fixed-effect model and random-effect model, the pooled sensitivity and specificity for [68Ga]Ga-FAPI-04 PET and [18F]FDG PET were reported as estimates with 95% confidence intervals (CIs). The I2 statistic was used to evaluate the heterogeneity among the pooled studies. The included studies' quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) approach. In all, 508 papers were found during the first search; ultimately, 12 studies totaling 224 patients were included. The pooled sensitivity of [68Ga]Ga-FAPI-04 PET and [18F]FDG PET for cancer recurrence were 0.97 (95% CI: 0.90-1.00) and 0.69 (95% CI: 0.60-0.77). The pooled sensitivity of [68Ga]Ga-FAPI-04 PET and [18F]FDG PET for gastrointestinal cancer recurrence were 1.00 (95% CI: 0.97-1.00) and 0.57 (95% CI: 0.42-0.74). The pooled specificity of [68Ga]Ga-FAPI-04 PET and [18F]FDG PET for gastrointestinal cancer recurrence were 0.66 (95% CI: 0.15-1.00) and 0.46 (95% CI, 0.00-1.00). Based on the previous studies, [68Ga]Ga-FAPI-04 PET shows higher sensitivity compared to [18F]FDG PET in detecting tumor recurrence, especially in detecting gastrointestinal cancer recurrence. [68Ga]Ga-FAPI-04 PET shows similar specificity compared to [18F]FDG PET in detecting gastrointestinal cancer recurrence. The detection results, however, came from investigations using modest sample numbers. In this matter, more extensive prospective study is required.

Current Applications and Future Directions of Circulating Tumor Cells in Colorectal Cancer Recurrence.

The ability to predict or detect colorectal cancer (CRC) recurrence early after surgery enables physicians to apply appropriate treatment plans and different follow-up strategies to improve patient survival. Overall, 30-50% of CRC patients experience cancer recurrence after radical surgery, but current surveillance tools have limitations in the precise and early detection of cancer recurrence. Circulating tumor cells (CTCs) are cancer cells that detach from the primary tumor and enter the bloodstream. These can provide real-time information on disease status. CTCs might become novel markers for predicting CRC recurrence and, more importantly, for making decisions about additional adjuvant chemotherapy. In this review, the clinical application of CTCs as a therapeutic marker for stage II CRC is described. It then discusses the utility of CTCs for monitoring cancer recurrence in advanced rectal cancer patients who undergo neoadjuvant chemoradiotherapy. Finally, it discusses the roles of CTC subtypes and CTCs combined with clinicopathological factors in establishing a multimarker model for predicting CRC recurrence.

Natural language processing for automated breast cancer recurrence detection and classification in computed tomography reports.

e13591 Background: Relapse is a major concern for oncologists and breast cancer survivors that necessitates additional treatment and often leads to mortality. Cancer registries routinely track cancer mortality, but few monitor for relapse because of logistical challenges and prohibitive costs. In this context, Natural Language Processing (NLP) is a promising tool. Merging artificial intelligence with linguistics, NLP can rapidly analyze vast volumes of text in electronic health records. This capability of NLP is particularly valuable for Computed Tomography (CT) scans used in breast cancer care. CT scans are routinely used to characterize breast cancer progression and are described in transcribed dictations by radiologists. We aimed to apply NLP to these text reports to identify breast cancer relapses. Objective: To automate breast cancer relapse detection and classification in CT text reports using NLP. Methods: We analyzed 1,445 CT text reports from patients diagnosed with breast cancer between January 1, 2005, and December 31, 2014. These reports underwent manual review by trained human annotators. Text was annotated to identify terminology defining local, regional, and distant breast cancer relapses. Annotated reports were partitioned into a training-validation set (90% cohort) and a test set (10% cohort) for NLP model development. Results: In our dataset of 1,445 CT text reports, 72 (5.0%) were classified as local relapse, 97 (6.7%) as regional relapse, and 743 (51.4%) as distant relapse. The performance of our NLP model using the training-validation dataset can be summarized by the following metrics and 95% confidence intervals: 94% (±3.2) accuracy for detection and 96% (±2.9) accuracy for classification. The performance of our NLP model was confirmed using the test dataset, with 90% (±4.5) accuracy for detection and 91% (±6.3) accuracy for classification. For reference, all metrics are outlined (Table). Conclusions: Our model for identifying regional and distant relapses in CT reports had excellent performance, but had lower sensitivity for local relapses, posing a risk of false negatives. Automating the identification and classification of breast cancer relapses, if used retrospectively, can enhance cancer registry data about patient outcomes and, if used prospectively, holds the potential for enhancing patient care. [Table: see text]

The Expression of TP63 as a Biomarker of Early Recurrence in Resected Esophageal Squamous Cell Carcinoma after Neoadjuvant Chemoradiotherapy.

Esophageal cancer ranks among the ten most common cancers worldwide. Despite the adoption of neoadjuvant concurrent chemoradiotherapy (nCCRT) followed by surgery as the standard treatment approach in recent years, the local recurrence rate remains high. In this study, we employed RNA-seq to investigate distinctive gene expression profiles in esophageal squamous cell carcinoma (ESCC) with or without recurrence following a standard treatment course. Our findings indicate that recurrent ESCC exhibits heightened keratinizing and epidermis development activity compared to non-recurrent ESCC. We identified TP63 as a potential candidate for distinguishing clinical outcomes. Furthermore, immunohistochemistry confirmed the trend of TP63 overexpression in ESCC recurrence. Patients with elevated TP63 expression had poorer overall survival and lower 3-year recurrence-free survival. This study underscores the potential of TP63 as a biomarker for detecting cancer recurrence and suggests its role in guiding future treatment options.

Abstract PO5-04-07: Characteristics of patients with metastatic HR+/HER2+ breast cancer in a Kaiser Permanente observational multi-site cohort

Abstract Background: Approximately 10% of female breast cancer and 13% of male breast cancer tumors express hormone-receptor positive/human epidermal growth factor receptor 2 positive (HR+/HER2+) molecular subtype. Since HER2+ targeted agents were made available nearly 10 years ago, there has been limited innovation in treatment of patients with HR+/HER2+ metastatic breast cancer (mBC) to improve clinical outcomes. This study aims to characterize the HR+/HER2+ mBC patient population by describing demographic and clinical characteristics and treatment patterns in a racially diverse, insured, population-based cohort. This study includes data from 4 regions of the Kaiser Permanente (KP) health system – Northwest, Northern California, Southern California, and Colorado. Methods: Eligible study patients were adults age > 18 years with HR+/HER2+ invasive breast cancer who were either initially diagnosed with Stage IV disease or were diagnosed at an earlier stage and experienced recurrence with distant metastasis between 6/8/2012 and 12/31/2019 with data collected through 12/31/2021. Select information was extracted from electronic health records (EHR) of eligible patients and combined with manually abstracted data to create the analytic dataset. Breast cancer recurrence was identified by tumor registrars or obtained through a breast cancer recurrence detection algorithm and verified by chart review. Chart reviewers collected data on metastatic sites, disease progression, reasons for stopping systemic therapy medications, and verified use of medications. Preliminary results: During the study period, we identified 492 subjects with HR+/HER2+ mBC. Seven were men and 485 were women. 221 (45%) had de novo Stage IV breast cancer at diagnosis and 271 (55%) had recurrent mBC. Median age at metastatic diagnosis was 59 years for de novo cases and 62 years for recurrent cases. The cohort was racially and ethnically diverse, with 13% Asian subjects (11% de novo, 15% recurrent), 12% Black subjects (10% de novo, 14% recurrent), and 66% White subjects (71% de novo, 63% recurrent). 18% of cases were recorded as Hispanic (19% de novo, 18% recurrent) in the EHR. Major sites of metastases, including bone, liver, lung, brain, and distant lymph nodes, were similar in both the de novo and recurrent groups. Among women (see table below), 28 (6%) received no systemic treatment for their metastatic disease (9% de novo, 3% recurrent). Among women with systemic treatment, 80% received anti-HER2 agents (90% de novo, 73% recurrent). Of women with recurrent mBC who received systemic therapy, 56% had received anti-HER2 therapy in the adjuvant setting. Conclusion: This population-based study of a racially diverse cohort examined EHR-derived data to describe current demographics and treatment patterns for HR+/HER2+ mBC in an insured patient population. Over 90% of women received systemic therapy, and the majority of those received anti-HER2 therapy per current treatment guidelines. Future analyses will focus on clinical outcomes in this cohort with a goal of informing how prognosis can be improved. Table. Citation Format: Sheila Weinmann, Debra Ritzwoller, Marilyn Kwan, Reina Haque, Stella Stergiopoulos, Ashley Cha, Eric Gauthier, Daniel Sapp, John Dickerson, Kathryn Richert-Boe, Weiming Hu, Nikki Carroll, Lie Hong Chen, Valerie Lee, Ravi Zalavadia, Maureen O'Keeffe-Rosetti. Characteristics of patients with metastatic HR+/HER2+ breast cancer in a Kaiser Permanente observational multi-site cohort [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-04-07.

Abstract 2416: Personalized minimal residual disease detection using tumor-derived structural variants in cell-free DNA

Abstract We demonstrate development and technical validation of a novel approach for analysis of plasma circulating-tumor DNA (ctDNA) for residual disease detection and monitoring that offers improvements over existing technologies. ctDNA in blood can be leveraged to monitor treatment response, detect cancer recurrence, and inform treatment decisions for cancer patients. However, accurate detection and quantification of ctDNA is technically challenging due to low concentration of plasma DNA, especially in the adjuvant setting. Most current assays rely on interrogating multiple patient-specific point mutations to achieve exquisite limits of detection but struggle with polymerase errors, sequencing artifacts and limited conversion of input DNA. To overcome these challenges, we developed an approach called Structural Variant Enrichment and Normalization (SVEN) that targets patient-specific genomic rearrangements to achieve sensitive detection and quantification of plasma ctDNA. This method leverages intrinsic features of tumor-derived structural variants (SVs) to improve enrichment and confidence of detection at low tumor fraction through multiplexed PCR and amplicon-based next generation sequencing. To evaluate the assay, we performed whole genome sequencing of DNA from two breast cancer cell lines, as well as matched FFPE tumor and buffy coat samples from 21 early-stage breast cancer patients. We identified consensus SVs, and designed multiplexed SV-specific primers for each subject. We then conducted PCR amplification of cell-free DNA followed by sequencing, amplicon identification, and quantification. Analytical validation was conducted using 284 replicates of cell line dilutions from 1% to 0.003%, and 5 to 40 ng of input. We developed multiplexed assays targeting 25 and 32 SVs across two cell lines, and 3 - 43 SVs across breast cancer patients (median 23 per patient). 91% and 42% of PCR targets were successfully validated for cell lines and FFPE samples respectively. Cell line dilutions demonstrated a sensitivity of 89% at 0.003% tumor fraction with 10 ng input or more. Tumor fractions measured using SVEN agreed with known values (R2 = 0.989). Application of validated panels to patient plasma samples and tumor/germline dilutions is ongoing. SVEN is a novel approach for tumor-guided ctDNA detection and quantification with potential relevance for residual disease detection. On-going studies are investigating the performance of this approach for ctDNA detection in patients with early and locally advanced breast cancer treated with neoadjuvant therapy. Citation Format: Bradon R. McDonald, Kirsten L. Dennison, Amanda L. Schussman, Stephanie M. McGregor, Barbara A. Pockaj, Muhammed Murtaza. Personalized minimal residual disease detection using tumor-derived structural variants in cell-free DNA [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 2416.

Abstract 3675: Design of high-performance tumor-informed minimal residual disease (MRD) panels from low FFPE tumor input

Abstract Background: Minimal residual disease (MRD) testing can detect cancer recurrence months to years earlier than the current standard of care, enabling earlier treatment of recurrence and improved patient outcomes. Tumor-informed MRD assays typically utilize formalin-fixed paraffin-embedded (FFPE) tumor tissue, which is available in limited quantities for some patients, for example, following core needle biopsy (CNB), after neoadjuvant treatment or when patients need multiple tests from the same tumor sample. To determine the lower limit of tissue input, we evaluated our MRD assay performance across a range of extracted tumor volumes. Methods: Resected tumors and CNBs were sectioned, H&E stained, and macro-dissected. Tumor gDNA was extracted, quantified, prepared into libraries and sequenced. Sequenced libraries were aligned and evaluated for depth of coverage, variation of coverage, and duplication rate. Somatic calling was performed on matched tumor and normal samples. Up to 1000 target sites were selected for high-depth targeted sequencing of the tumor and normal gDNA for confirmation of somatic variant calls. The positive predictive value (PPV) was computed as the percent of putative somatic variant sites that were present in the tumor capture library and absent in the normal capture library. Results: Extracted tumor volumes varied by almost two orders of magnitude, from 0.06mm3 (equivalent to needle core or fine needle aspirate biopsies) to 5mm3 (achievable with resected tumor). gDNA amount varied linearly (3.6ng to 1549ng) with tumor tissue input, indicating the low tissue to paraffin ratio did not have an adverse effect on yield. Tumor gDNA inputs into library prep ranged from 2.5ng to 100ng. DNA amounts above 100ng into library prep had no discernable benefit. Below 10 ng, depth of coverage and the coefficient of variation in coverage indicated poor-quality libraries. Samples with ~10 ng of gDNA input into library prep showed depth of coverage comparable to higher inputs and saturated the achievable library complexity. Additionally, PPV of somatic calling was consistent across the range of gDNA inputs from 10-100 ng, demonstrating equivalent assay performance. Conclusion: Tumor-informed MRD assays have immense potential for increasingly sensitive treatment response and recurrence monitoring that can inform better treatment decisions. FFPE tumor tissue is a critical input into MRD assays but is a limited resource. This study supports a minimum DNA input of 10 nanograms for a single attempt at extraction, corresponding to a tissue volume of 0.2mm3 or a single 10µm slide with a 20mm2 area, representing one of the lowest tissue input requirements for an MRD assay. Low FFPE tissue requirements expand the patient population that benefit from MRD testing by utilizing samples that have low tumor content, are post-neoadjuvant therapy or do not meet the tumor volume requirements of competing MRD offerings. Citation Format: Matt LaBella, Ashley Acevedo, Ravi Patel, Kiefer Haug, Sangita Ganesh, Elise Buser, Nafei Xu, Shalee Carlson, Kyle Trettin, Sarah Ratzel, Kieko Hara, Pavlos Msaouel, Kanishka Sircar, Chad Tang, Dale Muzzey, Genevieve Gould. Design of high-performance tumor-informed minimal residual disease (MRD) panels from low FFPE tumor input [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 3675.

Consideration of liquid biomarkers for surveillance of HPV-related oropharyngeal cancer in veteran populations

The incidence of human papillomavirus (HPV)-related oropharyngeal squamous cell carcinoma (OPSCC) will continue to rise in the United States over the next several decades. Thus, efforts to reduce treatment intensity, mitigate long-term physical and psychological sequelae of treatment, and simplify surveillance regimens for patients with HPV-related OPSCC are critical. Liquid biomarkers, namely plasma circulating tumor HPV DNA (ctDNA), have shown considerable promise for improvements in these domains by guiding personalized and adaptive treatment de-escalation paradigms and predicting disease recurrence in the survivorship period. Preliminary reports suggest an even broader impact of plasma HPV ctDNA assays for HPV-related OPSCC surveillance beyond the mere detection of cancer recurrence and metastasis. For instance, such assays may reduce the need for costly imaging studies, alleviate the financial toxicities of survivorship care, and improve care access and patient satisfaction. Currently, veterans and underserved populations are disproportionately affected by the financial burden of cancer surveillance and survivorship care. These disparities negatively impact oncologic outcomes, healthcare access, and utilization, specifically among veterans with HPV-related OPSCC. As such, we posit that HPV ctDNA monitoring may be of unique benefit and impact in the surveillance period for these patients specifically. Herein, we provide a narrative review of the current literature supporting the formal clinical evaluation of HPV ctDNA monitoring in veterans with HPV-related OPSCC.

Papillary Thyroid Microcarcinoma: Differences between Lesions in Incidental and Nonincidental Settings-Considerations on These Clinical Entities and Personal Experience.

Papillary thyroid microcarcinoma (PTMC) represents 35-40% of all papillary cancers; it is defined as a nodule ≤ 10 mm at the time of histological diagnosis. The clinical significance of PTMC is still controversial, and it may be discovered in two settings: incidental PTMC (iPTMC), in which it is identified postoperatively upon histological examination of thyroid specimens following thyroid surgery for benign disease, and nonincidental PTMC (niPTMC), in which it is diagnosed before surgery. While iPTMC appears to be related to mild behavior and favorable clinical outcomes, niPTMC may exhibit markers of aggressiveness. We retrospectively review our experience, selecting 54 PTMCs: 28 classified as niPTMC (52%) and 26 classified as iPTMC (48%). Patients with niPTMC showed significant differences, such as younger age at diagnosis (p < 0.001); a lower male/female ratio (p < 0.01); a larger mean nodule diameter (p < 0.001); and a higher rate of aggressive pathological findings, such as multifocality, capsular invasion and/or lymphovascular invasion (p = 0.035). Other differences found in the niPTMC subgroup included a higher preoperative serum TSH level, higher hospital morbidity and a greater need for postoperative iodine ablation therapy (p < 0.05), while disease-free long-term survival did not differ between subgroups (p = 0.331) after a mean follow-up (FU) of 87 months, with one nodal recurrence among niPTMCs. The differences between iPTMC and niPTMC were consistent: patients operated on for total thyroidectomy and showing iPTMC can be considered healed after surgery, and follow-up should be designed to properly calibrate hormonal supplementation; conversely, niPTMC may sometimes exhibit aggressive behavior, and so the FU regimen should be closer and aimed at early detection of cancer recurrence.

Increased blood CSF3R+ myeloid-derived suppressor cell is a predictor for breast cancer recurrence.

Early detection of cancer recurrence using specific biomarkers remains a clinically unmet need, although methodologies for monitoring tumor markers, cell-free DNA, and circulating tumor cells have been established for decades. Tumor recurrence develops in metastatic or dormant cancer cells under continuous immune surveillance. Alterations in the population and function of immune cells may contribute to cancer recurrence. Here, we utilized an animal model to imitate breast tumor recurrence after surgical resection and investigated the abundance and gene expression profiles of immune cells using NanoString analysis. Bioinformatic analysis of a published single-cell RNA sequencing database of myeloid-derived suppressor cells (MDSCs) was performed to identify common targets between the two studies. Identified biomarkers were validated using human peripheral blood mononuclear cell (PBMC) datasets. The inhibitory effect of MDSCs on T-cell proliferation was assessed in vitro. Our data demonstrated that the number of MDSCs significantly increased during recurrence. Comparison of our NanoString data with a single-cell RNA sequencing dataset of MDSCs in another spontaneous breast cancer model identified colony-stimulating factor 3 receptor (Csf3r)-positive MDSCs as a potential marker for predicting tumor relapse. We validated our findings using two previously published PBMC databases of patients with breast cancer with or without recurrence and confirmed the elevated MDSC gene signature and CSF3R expression in patients with tumor recurrence. 35 patients with breast cancer were also included in our study, that patients with higher levels of CSF3R had worse survival. In vitro experiments demonstrated that Csf3r + MDSCs exhibited enhanced reactive oxygen species (ROS) levels and robust T-cell suppression ability. We conclude that an increase in CSF3R + MDSCs is a potential biomarker for early detection of tumor recurrence in patients with breast cancer.

Explorative cost-effectiveness analysis of colorectal cancer recurrence detection with next-generation sequencing liquid biopsy in Spain, France, and Germany.

Next-generation sequencing liquid biopsy (NGS-LB) for colorectal cancer (CRC) detection and surveillance remains an expensive technology as economies of scale have not yet been realized. Nevertheless, the cost of sequencing has decreased while sensitivity has increased, raising the question of whether cost-effectiveness (CE) has already been achieved from the perspective of European healthcare systems. This health economic (HE) modeling study explores the CE of NGS-LB for CRC based on direct treatment costs compared to standard care without liquid biopsy in Spain, France, and Germany. A structured literature search was used to collect evidence from 2009 to 2020 on the stage-dependent quality of life (quality-adjusted life-years, QALY), efficacy, and total direct treatment costs (TDC) of NGS-LB. A decision-analytic Markov model was developed. Over the remaining lifetime, cumulative life expectancy (LE), TDC, and QALYs were calculated for 60-year-old men and women in CRC stage III with different assumed effects of NGS-LB of 1% or 3% on improved survival and reduced stage progression, respectively. The use of NGS-LB increases LE by 0.19 years in Spanish men (France: 0.19 years, Germany: 0.13 years) and by 0.21 years in Spanish women (France: 0.21 years, Germany: 0.14 years), respectively. The 3% discounted cost per QALY gained was 35,571.95 € for Spanish men (France: 31,705.15 €, Germany: 37,537.68 €) and 35,435.71 € for Spanish women (France: 31,295.57 €, Germany: 38,137.08 €) in the scenario with 3% improved survival and reduced disease progression. Compared to the other two countries, Germany has by far the highest TDC, which can amount to >80k euros in the last treatment year. In this explorative HE modeling study, NGS-LB achieves generally accepted CE levels in CRC treatment from the health system perspective in three major European economies under assumptions of small improvements in cancer recurrence and survival. Confirmation of these findings through clinical trials is encouraged.

Upper Tract Urothelial Carcinoma: A Narrative Review of Current Surveillance Strategies for Non-Metastatic Disease.

Non-metastatic upper urinary tract carcinoma (UTUC) is a comparatively rare condition, typically managed with either kidney-sparing surgery (KSS) or radical nephroureterectomy (RNU). Irrespective of the chosen therapeutic modality, patients with UTUC remain at risk of recurrence in the bladder; in patients treated with KSS, the risk of recurrence is high in the remnant ipsilateral upper tract system but there is a low but existent risk in the contralateral system as well as in the chest and in the abdomen/pelvis. For patients treated with RNU for high-risk UTUC, the risk of recurrence in the chest, abdomen, and pelvis, as well as the contralateral UT, depends on the tumor stage, grade, and nodal status. Hence, implementing a risk-stratified, location-specific follow-up is indicated to ensure timely detection of cancer recurrence. However, there are no data on the type and frequency/schedule of follow-up or on the impact of the recurrence type and site on outcomes; indeed, it is not well known whether imaging-detected asymptomatic recurrences confer a better outcome than recurrences detected due to symptoms/signs. Novel imaging techniques and more precise risk stratification methods based on time-dependent probabilistic events hold significant promise for making a cost-efficient individualized, patient-centered, outcomes-oriented follow-up strategy possible. We show and discuss the follow-up protocols of the major urologic societies.

Untargeted Metabolomic Study of Lung Cancer Patients after Surgery with Curative Intent.

Lung cancer (LC) is a leading cause of mortality, claiming more than 1.8 million deaths per year worldwide. Surgery is one of the most effective treatments when the disease is in its early stages. The study of metabolic alterations after surgical intervention with curative intent could be used to assess the response to treatment or the detection of cancer recurrence. In this study, we have evaluated the metabolomic profile of serum samples (n = 110) from preoperative (PRE) and postoperative (POST) LC patients collected at two different time points (1 month, A; 3-6 months, B) with respect to healthy people. An untargeted metabolomic platform based on reversed phase (RP) and hydrophilic interaction chromatography (HILIC), using ultra-high performance liquid chromatography (UHPLC) and mass spectrometry (MS), was applied (MassIVE ID MSV000092213). Twenty-two altered metabolites were annotated by comparing all the different studied groups. DG(14,0/22:1), stearamide, proline, and E,e-carotene-3,3'-dione were found altered in PRE, and their levels returned to those of a baseline control group 3-6 months after surgery. Furthermore, 3-galactosyllactose levels remained altered after intervention in some patients. This study provides unique insights into the metabolic profiles of LC patients after surgery at two different time points by combining complementary analytical methods.

Mutated TP53 in Circulating Tumor DNA as a Risk Level Biomarker in Head and Neck Squamous Cell Carcinoma Patients.

Circulating tumor DNA (ctDNA) has been suggested as a surrogate biomarker for early detection of cancer recurrence. We aimed to explore the utility of ctDNA as a noninvasive prognostic biomarker in newly diagnosed head and neck squamous cell carcinoma (HNSCC) patients. Seventy HNSCC specimens were analysed for the detection of TP53 genetic alterations utilizing next-generation sequencing (NGS). TP53 mutations were revealed in 55 (79%). Upon detection of a significant TP53 mutation, circulating cell-free DNA was scrutinized for the presence of the tumor-specific mutation. ctDNA was identified at a minimal allele frequency of 0.08% in 21 out of 30 processed plasma samples. Detectable ctDNA correlated with regional spread (N stage ≥ 1, p = 0.011) and poorer 5-year progression-free survival (20%, 95% CI 10.9 to 28.9, p = 0.034). The high-risk worst pattern of invasion (WPOI grade 4-5) and deep invasion were frequently found in patients whose ctDNA was detected (p = 0.087 and p = 0.072, respectively). Detecting mutated TP53 ctDNA was associated with poor progression-free survival and regional metastases, indicating its potential role as a prognostic biomarker. However, ctDNA detectability in early-stage disease and the mechanisms modulating its release into the bloodstream must be further elucidated.

Detection of Cancer Recurrence Using Systemic Inflammatory Markers and Machine Learning after Concurrent Chemoradiotherapy for Head and Neck Cancers.

Pretreatment values of the neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR) are well-established prognosticators in various cancers, including head and neck cancers. However, there are no studies on whether temporal changes in the NLR and PLR values after treatment are related to the development of recurrence. Therefore, in this study, we aimed to develop a deep neural network (DNN) model to discern cancer recurrence from temporal NLR and PLR values during follow-up after concurrent chemoradiotherapy (CCRT) and to evaluate the model's performance compared with conventional machine learning (ML) models. Along with conventional ML models such as logistic regression (LR), random forest (RF), and gradient boosting (GB), the DNN model to discern recurrences was trained using a dataset of 778 consecutive patients with primary head and neck cancers who received CCRT. There were 16 input features used, including 12 laboratory values related to the NLR and the PLR. Along with the original training dataset (N = 778), data were augmented to split the training dataset (N = 900). The model performance was measured using ROC-AUC and PR-AUC values. External validation was performed using a dataset of 173 patients from an unrelated external institution. The ROC-AUC and PR-AUC values of the DNN model were 0.828 ± 0.032 and 0.663 ± 0.069, respectively, in the original training dataset, which were higher than the ROC-AUC and PR-AUC values of the LR, RF, and GB models in the original training dataset. With the recursive feature elimination (RFE) algorithm, five input features were selected. The ROC-AUC and PR-AUC values of the DNN-RFE model were higher than those of the original DNN model (0.883 ± 0.027 and 0.778 ± 0.042, respectively). The ROC-AUC and PR-AUC values of the DNN-RFE model trained with a split dataset were 0.889 ± 0.032 and 0.771 ± 0.044, respectively. In the external validation, the ROC-AUC values of the DNN-RFE model trained with the original dataset and the same model trained with the split dataset were 0.710 and 0.784, respectively. The DNN model with feature selection using the RFE algorithm showed the best performance among the ML models to discern a recurrence after CCRT in patients with head and neck cancers. Data augmentation by splitting training data was helpful for model performance. The performance of the DNN-RFE model was also validated with an external dataset.

Large healthy donor dataset demonstrates high analytical specificity and repeatability for the NeXT Personal molecular residual disease assay.

e15031 Background: Residual and recurrent cancer detection using circulating cell-free DNA (cfDNA) in liquid biopsy samples has proven promising in the past decade, with emerging technologies driving increasingly lower limits of detection (LOD). At ultra-high detection sensitivity levels, it is critical to warrant a high specificity to ensure that the detected signals are true measurements of the residual disease. Methods: The molecular residual disease (MRD) detection application of the NeXT Personal platform relies on up to 1,800 personalized somatic variants identified by whole genome sequencing (WGS) of the patient-specific tumor compared with the matched normal sample. Under the assumption that individuals with undetectable cancer should have negative MRD detection, we evaluated the MRD analytical specificity of the assay by measuring background noise using over 200 patient-specific panel designs to a large cohort of healthy donors that should display no tumor signals at any MRD target loci. These panels were designed and manufactured based on a pan-cancer cohort of tumor-normal paired samples whole genome data. Then, those designed panels were evaluated on cfDNA extracted from the plasma of over 200 unique healthy donors. 30-50 ng (median 50 ng) of cfDNA was used for the assay for each sample. Furthermore, six of the 200 patient panels were used to measure assay repeatability by hybridizing to at least 28 different healthy donors per panel. Results: The pan-cancer cohort used for panel design was composed of predominantly stage II ~ IV patients from 12 distinct tumor types. Across all patient samples, no MRD was detected, resulting in 100% specificity (95% confidence interval: 98.23-100%). In addition to the 100% specificity observed, the median anticipated limit of detection (LOD) as calculated by the number of targets and the number of molecules at each target was 2.6 PPM, with the lowest LOD being 1.4 PPM. The average observed unexpected signal was nearly one order of magnitude lower than the average LOD of each panel. Lower LODs were associated with larger panels (up to 1,800 mutation targets) and higher tumor purity. No correlation was observed between noise and tumor type of the designed panels or healthy plasma donor age. Further, we observed 100% repeatability across the six panels that were each applied to at least 28 unique plasma donors, with MRD not being detected in any of the replicates. Conclusions: The large healthy donor screening study demonstrated that our assay maintains excellent specificity and repeatability while still achieving ultra-sensitive detection. In all cases, the observed error-rates in the panels were very low and did not affect detection specificity. Overall these landmark specificity and repeatability results lend further confidence to the robustness of the analytical performance of NeXT Personal.

High rates of detection of metastatic/recurrent colorectal cancer on clinical imaging at the time of molecular residual disease testing following operative management.

e15543 Background: Detection of circulating tumor DNA (ctDNA) following operative management for colorectal cancer (CRC) as part of molecular residual disease (MRD) assays has shown significant prognostic implications. The majority of studies examining the time to detection of cancer recurrence have been done retrospectively without the treating physician knowing the results of the assay. Limited prospective data exists regarding the probability of detecting cancer on imaging at the time of a positive MRD test following operative management of all sites of disease. Here, we analyze the association of positive MRD testing with imaging findings of recurrent or metastatic CRC using a cohort of patients that underwent prospective MRD testing. Methods: Patients with stage I-IV intestinal cancers at University of Wisconsin Carbone Cancer Center who underwent prospective Natera Signatera MRD testing following operative management of their disease were identified and consented to an IRB-approved registry protocol. Those consented patients who had a positive test without being on systemic therapy and had clinical imaging within 45 days were analyzed further. The presence of definitive cancer, indeterminate findings, and no evidence of cancer was recorded per the treating physician using standard of care clinical imaging. The presence of cancer on imaging was then correlated with the quantity of ctDNA (mean tumor molecules (MTM)/ml). Results: 163 patients with stage I-IV CRC and 1 small intestinal cancer underwent MRD testing. 30 positive ctDNA tests with imaging were available across 22 unique patients (median age 54 years (29-84) 7 females). 23 samples were in the resected metastatic setting, 5 stage III and 2 stage I. Cancer was seen on imaging in 19/30 (63%) of positive tests, indeterminate in 3 (10%) and negative for cancer in 9/30 (27%). With ctDNA levels &gt; 10 MTM/ml (n = 7), cancer was detected on imaging in all cases. With ctDNA levels of 1-10 MTM/ml cancer was detected in 42% and at &lt; 1 MTM/ml in 64%. A trend towards greater detection of cancer was observed when MRI or PET/CT was performed. Radiologic disease detection in patients with positive MRD analysis was higher in those with stage IV disease (70%) vs. stage I-III (43%). Conclusions: ctDNA MRD positivity is associated with high rates of detection of recurrent/metastatic CRC, especially in patients with resected stage IV disease and with a quantity of &gt; 10 MTM/ml. Clinical imaging should be considered at the time of detection of ctDNA.