Predict Disease Recurrence Research Articles

Electronic health record (EHR)-based machine learning (ML) to predict disease recurrence after surgical resection of early-stage non-small cell lung cancer (eNSCLC).

6626 Background: Surgical resection (SR) is a guideline-recommended definitive therapy for patients (pts) with eNSCLC. However, 30–50% pts develop disease recurrence (DR) within the first 5 years (yrs) after surgery. ML applied to routinely collected EHR data could facilitate timely identification of pts at risk of DR who would benefit from enhanced surveillance or initial treatment (Tx) intensification. Methods: eNSCLC pts with stage IB-IIIA at the time of SR between Jan 2010 – February 2022 were identified from ConcertAI Patient360 oncology database comprising structured and curated records from US-based EHR. DR was defined as the human-curated earliest advanced/metastatic diagnosis date from SR. Gradient boosting (GB), random forest (RF), and logistic regression (LR) algorithms with 6-fold nested cross-validation were trained and compared to predict the risk of DR or death at 2 yrs from SR. Pts who did not experience DR and were lost to follow-up within 2 yrs from SR were removed. Feature importance was defined using Shapley Additive Explanation (SHAP)-derived odds ratios (OR). Due to low prevalence of DR at 2 yrs, AUPRC was used as performance metric. Pts in the 1st and 4th quartiles of predicted probabilities from XGB model were defined as low-risk vs. high-risk groups. Results: Among 3597 pts, median age was 68.3 yrs (IQR 12.5), 51.8% were female, and 8.6% were Black. 24.4% developed DR within 2 yrs. GB, RF, and LR models had similar ability to predict DR at 2 yrs with mean hold-out set AUPRC of 0.33. In GB model, DR prevalence at 2 yrs was 34% in the high-risk vs. 18% in the low-risk group in hold-out set. N0 stage, T stage < 3, receipt of adjuvant immune checkpoint inhibitor (ICI), and presence of EGFR mutations were protective against DR at 2 yrs, while history of anemia and congestive heart failure (CHF) were risk factors (Table). SHAP revealed a N stage-by-adjuvant therapy and a N stage-by-CHF interaction: benefit from adjuvant chemotherapy (CT) was limited to higher N stages, while adjuvant ICI was beneficial for all N stages. CHF was a risk factor for lower N stages but not for higher N stages. Conclusions: ML applied to structured and unstructuredEHRs identified predictors of risk of DR at 2 yrs after surgery in eNSCLC and may identify high-risk pts who would benefit from enhanced surveillance plans and Tx intensification in the eNSCLC setting. The model indicated favorable outcome from adjuvant targeted therapies in EGFR mutated pts. [Table: see text]

Circulating tumor DNA–based detection of molecular residual disease as a biomarker for recurrence monitoring predict disease recurrence in patients with ovarian cancer.

e17542 Background: Despite recent advances in cancer diagnostics and treatments, nearly 75% ovarian cancer patients relapse within two years of primary therapy and become candidates for treatment of recurrent diseases. A novel approach to post-surgical risk stratification for molecular residual disease (MRD) detection and treatment monitoring is needed to improve patient outcomes. Methods: We analyzed a cohort of 22 stage Ⅰ-Ⅳ ovarian cancer patients which were followed up at median 6 (range,3-15) times between July 2017 and December 2020. Among the 22 patients, stage I, II, III and Ⅳ comprised 9%, 5%, 50% and 36%, respectively. Tumor tissue and blood samples of all subjects were collected at Ruijin Hospital, Shanghai Jiao Tong University.Somatic mutations were identified by whole exome sequencing and assessed from plasma collected during treatment using personalized tumor-informed MRDtect assays with a median of 25（range,17-30） amplicons/assay targeting tumor-specific variants unique to each patient, sequenced at mean 200,000X depth. Plasma samples with ≥2 variants detected were considered MRD-positive and ctDNA levels were reported in mean tumor molecules per mL (MTM/mL) of plasma. Sequencing data were analyzed using PiVAT secondary analysis software and MRD positive was concluded when at least two variants were detected in plasma. Results: CtDNA was preoperatively detectable in 18 (85.7%) patients, and the positive rate became 38.8% (7/18) after surgery. Serial ctDNA analysis during surveillance after definitive treatment of the 22 patients with longitudinal collected plasma samples identified relapse with 100% sensitivity and 100% specificity. The median lead time from ctDNA detection in plasma to relapse detection by standard-of-care computed tomography was 135 days (range,45-387days). Variants from a total of 526 genes were selected from the WES results of these 22 patients. Among these 526 genes, 96% (505 genes) were selected for only one patient, 3.4% (18 genes) were selected for two patients and 0.2% (one gene) were selected for three patients. Compared with tumor-agnostic assay, tumor-informed assay is a more accurate route that is more consistent with the heterogeneity of tumor and can maximize the ability to reflect the real situation of each patient. Conclusions: Sensitive methods for risk stratification, therapeutic efficacy monitoring, and early relapse detection may have a major impact on treatment decisions and patient management for ovarian cancer patients. MRD can be used as an effective biomarker to prompt prognosis and recurrence risk, providing powerful assistance for accurate diagnosis and treatment for patients.

Molecular Testing Predicts Incomplete Response to Initial Therapy in Differentiated Thyroid Carcinoma Without Lateral Neck or Distant Metastasis at Presentation: Retrospective Cohort Study.

Background: Molecular testing (MT) is emerging as a potential prognostic factor that can be available before treatment of differentiated thyroid carcinoma begins. Among patients eligible for either lobectomy or total thyroidectomy as their initial therapy, our study aims were to assess (1) if conventionally available preoperative factors are associated with incomplete response to initial therapy, and (2) if MT results can be a surrogate for the ATA Risk Stratification System (RSS) to estimate risk of recurrence. Methods: The data of consecutive thyroid cancer patients without preoperative lateral neck disease or distant metastasis who underwent index thyroidectomy between November 1, 2017 and October 31, 2021 were reviewed. Logistic regression models including preoperative variables such as MT and/or the postoperatively available RSS were constructed to predict disease recurrence, either structural or biochemical. Model discrimination using the c-statistic and goodness-of-fit test were compared. Results: Among 945 patients studied, 50 (5.2%) recurred with 18-month median follow-up. Recurrences were detected in 17 (2.9%), 20 (6.7%), and 13 (22.8%) patients with RSS-low, -intermediate, and -high cancers, respectively (p < 0.001). In multivariable analysis, only tumor size was associated with recurrence (odds ratio [OR] 1.3, 95% confidence interval [CI] 1.1-1.5). In a different model analyzing 440 (46.6%) patients with available MT results, recurrence was associated with both larger tumor size (OR 1.4 [95% CI 1.1-1.8]) and MT results (p < 0.001). Including MT improved the c-statistic by 27%, which was statistically no different than the model incorporating only the RSS (p = 0.15). Conclusions: Disease recurrence was observed across all ATA RSS categories in short-term follow-up, and tumor size was the only conventional preoperative factor associated with recurrence. When MT results were incorporated, they not only improved predictive ability beyond tumor size alone, but also yielded similar ability as the gold standard ATA RSS. Thus, MT results might aid the development of novel preoperative risk stratification algorithms.

Prediction model on disease recurrence for low risk resected stage I lung adenocarcinoma.

Although stage I non-small cell lung carcinoma (NSCLC) typically carries a good prognosis following complete resection, early disease recurrence can occur. An accurate survival prediction model would help refine a follow-up strategy and personalize future adjuvant therapy. We developed a post-operative prediction model based on readily available clinical information for patients with stage I adenocarcinoma. We retrospectively studied the disease-free survival (DFS) of 408 patients with pathologically confirmed low-risk stage I adenocarcinoma of lung who underwent curative resection from 2013 to 2017. A tree-based method was employed to partition the cohort into subgroups with distinct DFS outcome and stepwise risk ratio. These covariates were included in multivariate analysis to build a scoring system to predict disease recurrence. The model was subsequently validated using a 2011-2012 cohort. Non-smoker status, stage IA disease, epidermal-growth factor receptor mutants and female gender were associated with better DFS. Multivariate analysis identified smoking status, disease stage and gender as factors necessary for the scoring system and yielded 3 distinct risk groups for DFS [99.4 (95% CI 78.3-125.3), 62.9 (95% CI 48.2-82.0), 33.7 (95% CI 24.6-46.1) months, p < 0.005]. External validation yielded an area under the curve by receiver operating characteristic analysis of 0.863 (95% CI 0.755-0.972). The model could categorize post-operative patients using readily available clinical information, and may help personalize a follow-up strategy and future adjuvant therapy.

Development and validation of prognostic dynamic nomograms for hepatitis B Virus-related hepatocellular carcinoma with microvascular invasion after curative resection.

The prediction models of postoperative survival for hepatitis B virus-related hepatocellular carcinoma (HBV-HCC) with microvascular invasion (MVI) have not been well established. The study objective was the development of nomograms to predict disease recurrence and overall survival (OS) in these patients. Data were obtained from 1046 HBV-related MVI-positive HCC patients who had undergone curative resection from January 2014 to December 2017. The study was approved by the Eastern Hepatobiliary Surgery Hospital and Jinling Hospital ethics committee, and patients provided informed consent for the use of their data. Nomograms for recurrence and OS were created by Cox regression model in the training cohort (n=530). The modes were verified in an internal validation cohort (n= 265) and an external validation cohort (n= 251). The nomograms of recurrence and OS based on preoperative serological indicators (HBV-DNA, neutrophil-lymphocyte ratio, a-fetoprotein), tumor clinicopathologic features (diameter, number), surgical margin and postoperative adjuvant TACE achieved high C-indexes of 0.722 (95% confidence interval [CI], 0.711-0.732) and 0.759 (95% CI, 0.747-0.771) in the training cohort, respectively, which were significantly higher than conventional HCC staging systems (BCLC, CNLC, HKLC).The nomograms were validated in the internal validation cohort (0.747 for recurrence, 0.758 for OS) and external validation cohort(0.719 for recurrence, 0.714 for OS) had well-fitted calibration curves. Our nomograms accurately stratified patients with HBV-HCC with MVI into low-, intermediate- and high-risk groups of postsurgical recurrence and mortality. Prediction models for recurrence-free survival (https://baishileiehbh.shinyapps.io/HBV-MVI-HCC-RFS/) and OS (https://baishileiehbh.shinyapps.io/HBV-MVI-HCC-OS/) were constructed. The two nomograms showed good predictive performance and accurately distinguished different recurrence and OS by the nomograms scores for HBV-HCC patients with MVI after resection.

Risk prediction of esophageal squamous cell carcinoma recurrence in patients who underwent esophagectomy after receiving neoadjuvant treatment: a nationwide retrospective study in Japan.

Although neoadjuvant treatment (NAT) has become the standard of care for patients with locally advanced esophageal cancer, the risk of recurrence remains high. The risk must be predicted accurately, so that appropriate adjuvant therapy can be planned. We aimed to develop a model predicting recurrence of esophageal squamous cell carcinoma (ESCC) in patients who received NAT before esophagectomy. This nationwide study included 3874 patients from 85 institutions. Patients who underwent NAT and then surgery for ESCC were eligible. We developed a Cox proportional hazards model and created a nomogram to predict disease recurrence after NAT and curative esophagectomy. Of the patients, 268 (6.9%), 1280 (33.0%), 2006 (51.8%), and 320 (8.3%) had clinical stage I, II, III, and IV tumors, respectively. The 5-year recurrence rate was 45.1% (95% confidence interval 43.4%-46.7%). Multivariable analysis revealed that body mass index, type of neoadjuvant treatment, primary tumor location, operative blood loss, pathological tumor stage, pathological therapeutic effect, and leakage were independently associated with disease recurrence. Using 13 commonly measured perioperative variables, we created a predictive nomogram, and the area under the curve was 0.783 (95% confidence interval 0.766-0.800). This nomogram was also adequately validated internally and had excellent calibration capacity (calibration slope, 0.992). The model developed in this study adequately predicted ESCC recurrence in patients who underwent NAT and then esophagectomy. Further research with this nomogram is needed to assess the effect of adjuvant therapy in patients at high risk for recurrence.

Predictive role of blood-based indicators in neuromyelitis optica spectrum disorders.

This study aimed to assess the predictive role of blood markers in neuromyelitis optica spectrum disorders (NMOSD). Data from patients with NMOSD, multiple sclerosis (MS), and healthy individuals were retrospectively collected in a 1:1:1 ratio. The expanded disability status scale (EDSS) score was used to assess the severity of the NMOSD upon admission. Receiver operating characteristic (ROC) curve analysis was used to distinguish NMOSD patients from healthy individuals, and active NMOSD from remitting NMOSD patients. Binary logistic regression analysis was used to evaluate risk factors that could be used to predict disease recurrence. Finally, Wilcoxon signed-rank test or matched-sample t-test was used to analyze the differences between the indicators in the remission and active phases in the same NMOSD patient. Among the 54 NMOSD patients, neutrophil count, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) (platelet × NLR) were significantly higher than those of MS patients and healthy individuals and positively correlated with the EDSS score of NMOSD patients at admission. PLR can be used to simultaneously distinguish between NMOSD patients in the active and remission phase. Eleven (20.4%) of the 54 patients had recurrence within 12 months. We found that monocyte-to-lymphocyte ratio (MLR) (AUC = 0.76, cut-off value = 0.34) could effectively predict NMOSD recurrence. Binary logistic regression analysis showed that a higher MLR at first admission was the only risk factor for recurrence (p = 0.027; OR = 1.173; 95% CI = 1.018-1.351). In patients in the relapsing phase, no significant changes in monocyte and lymphocyte count was observed from the first admission, whereas patients in remission had significantly higher levels than when they were first admitted. High PLR is a characteristic marker of active NMOSD, while high MLR is a risk factor for disease recurrence. These inexpensive indicators should be widely used in the diagnosis, prognosis, and judgment of treatment efficacy in NMOSD.

PD36-05 ASSESSMENT OF CIRCULATING TUMOR DNA STATUS AS A PROGNOSTIC MARKER FOR RECURRENCE DETECTION IN PATIENTS WITH MUSCLE INVASIVE BLADDER CANCER

You have accessJournal of UrologyCME1 Apr 2023PD36-05 ASSESSMENT OF CIRCULATING TUMOR DNA STATUS AS A PROGNOSTIC MARKER FOR RECURRENCE DETECTION IN PATIENTS WITH MUSCLE INVASIVE BLADDER CANCER Shivaram Cumarasamy, George Laliotis, Elshaddai White, Jordan Rich, Punashi Dutta, Shruti Sharma, Mark Calhoun, Adam Elnaggar, Minetta Liu, Kyrollis Attalla, Reza Mehrazin, Peter Wiklund, and John Sfakianos Shivaram CumarasamyShivaram Cumarasamy More articles by this author , George LaliotisGeorge Laliotis More articles by this author , Elshaddai WhiteElshaddai White More articles by this author , Jordan RichJordan Rich More articles by this author , Punashi DuttaPunashi Dutta More articles by this author , Shruti SharmaShruti Sharma More articles by this author , Mark CalhounMark Calhoun More articles by this author , Adam ElnaggarAdam Elnaggar More articles by this author , Minetta LiuMinetta Liu More articles by this author , Kyrollis AttallaKyrollis Attalla More articles by this author , Reza MehrazinReza Mehrazin More articles by this author , Peter WiklundPeter Wiklund More articles by this author , and John SfakianosJohn Sfakianos More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003334.05AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Though radical cystectomy (RC) is the gold standard treatment for patients with muscle invasive bladder cancer (MIBC), ∼50% of patients recur. Here, we aimed to elucidate the ability of circulating tumor DNA (ctDNA) as a prognostic biomarker to predict disease recurrence in patients who underwent RC. METHODS: ctDNA analysis was retrospectively performed in a cohort of 49 MIBC patients with a median age of 70 years (range: 46-88 years) and 81.63% (40/49) male. In this cohort, patients were subjected to RC alone (RC group, N=38) or neoadjuvant chemotherapy (NAC) followed by RC (NAC+RC group, N=11). A total of 62 blood samples were collected from 11/18/21 to 09/21/22 for a median follow-up of 8.01 months (range: 2.23 - 63.76 months). ctDNA was analyzed prior to (N=26) and after RC (N=36) using a personalized, tumor-informed ctDNA assay (SignateraTM, mPCR - NGS assay); its association with clinical outcomes was assessed. RESULTS: In this cohort, presurgical (baseline) mean MTM levels were significantly associated with advanced stage (III/IV) compared to early stage (I/II) disease, p=0.033 (Figure 1A). Among 26 and 36 patients with baseline and post-RC blood samples available, ctDNA detection rate was 34.6% (9/26) and 22.2% (8/36), respectively. ctDNA-positive patients were only observed in the RC group at both baseline (N=9) and post-RC (N=8). Clinical recurrence was observed in 22.2% (2/9) and 25% (2/8) of patients at the baseline and post-RC time points, respectively. Conversely, no recurrences were seen among the RC group who were ctDNA negative at both time points (NPV: 100%). Our data suggest that patients with ctDNA-positivity had a higher probability of recurrence (chi-square, p<0.001) (Figure 1B). On analyzing the association of ctDNA status post-RC with the survival benefit, ctDNA-positivity was associated with poorer recurrence free survival (RFS) (HR=13.13; 95%CI: 0.73 - 234, p=0.08) (Figure 1C). CONCLUSIONS: We report early results of presurgical (baseline) and post-RC ctDNA testing in patients with MIBC. ctDNA-negativity at both time points correlated with absence of disease recurrence. Further clinical evaluation with a longer follow-up is warranted to fully validate the role of baseline ctDNA in upfront clinical disease management. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e981 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Shivaram Cumarasamy More articles by this author George Laliotis More articles by this author Elshaddai White More articles by this author Jordan Rich More articles by this author Punashi Dutta More articles by this author Shruti Sharma More articles by this author Mark Calhoun More articles by this author Adam Elnaggar More articles by this author Minetta Liu More articles by this author Kyrollis Attalla More articles by this author Reza Mehrazin More articles by this author Peter Wiklund More articles by this author John Sfakianos More articles by this author Expand All Advertisement PDF downloadLoading ...

Research Progress of Next Generation Sequencing in Acute Leukemia --Review

With the advent of precision medicine, next-generation sequencing (NGS) is playing an increasingly important role in clinical oncology diagnosis and treatment with its advantages of high sensitivity, high accuracy, high efficiency and operability. NGS reveals the genetic characteristics of acute leukemia(AL) patients by screening for specific disease-causing genes to identify occult as well as complex genetic mutations in patients with AL, leading to early diagnosis and targeted drug therapy for AL patients, as well as to predict disease recurrence by detecting mnimal residual disease (MRD) and analyzing mutated genes to determine patient prognosis. NGS plays an increasingly important role in the diagnosis, treatment and prognosis assessment in AL, providing a direction for the pursuit of precision medicine. This paper reviews the research progress of NGS in AL.

Constructing a prediction model of inflammatory bowel disease recurrence based on factors affecting the quality of life.

This study aimed to determine the factors affecting the quality of life of patients with inflammatory bowel disease (IBD) and to construct a disease recurrence prediction model based on these influencing factors. A prospective, single-center study in China was conducted between October 2020 and March 2021. The quality of life of patients was assessed using the Inflammatory Bowel Disease Questionnaire (IBDQ). Multiple stepwise regression analysis was used to analyze the factors influencing the quality of life of patients with IBD. The chi-square test and the point-biserial correlation analysis were performed to identify factors associated with clinical recurrence. A binary logistic regression model was constructed to predict the recurrence. The receiver operating characteristic curve was used to evaluate the prediction model. Patients with IBD from April 2021 to June 2021 were randomly included for model verification to evaluate the disease recurrence prediction model. The average IBDQ score of patients with IBD was 172.2 ± 35.0 (decreased by 23.2%). The scores of all dimensions of the IBDQ were decreased, especially emotional function and systemic symptoms. Disease activity, age, extraintestinal manifestations (EIMs), and annual household income were important factors influencing the IBDQ scores of patients with ulcerative colitis, and these accounted for ~57.0% of the factors affecting the quality of life. Disease activity, EIMs, and occupational stress were important factors influencing the IBDQ scores of patients with Crohn's disease, and they accounted for approximately 75.1% of the factors affecting the quality of life. Annual household income, occupational stress, and IBDQ scores were independent risk factors for recurrence. The area under the curve of the recurrence prediction model was 81.1%. The sensitivity and specificity were 81.7 and 71.7%, respectively. The Youden index of the model was 0.534. The established recurrence prediction model has good discriminant validity in the validation cohort. The quality of life of patients with IBD was generally poor. The use of factors affecting the quality of life to predict disease recurrence has high predictive value and can support the management of IBD by selecting patients at a higher risk for relapse.

Abstract P3-05-48: Prediction of disease recurrence in low risk Oncotype Dx breast cancers from digital H&amp;E-stained whole slide images of pre-treatment resections alone

Abstract Background Breast cancer patients with estrogen receptor (ER)+/HER2- (and usually node-negative) tumors can avail themselves of Oncotype DX Breast Recurrence Score (ODXRS) testing to predict their risk of distant recurrence within 9 years and, consequently, putative chemotherapy benefit. However, ODXRS testing requires sufficient tumour availability and specimen shipping, which imposes time and financial burdens to testing which have to be met by healthcare systems. The advent of digital pathology offers a potential avenue for exploring computer-aided diagnostic solutions which may overcome these hurdles by extracting the requisite information from hematoxylin and eosin (H&amp;E)-stained tissue whole slide images (WSIs) alone. In turn, this technology could significantly reduce diagnostic turnaround times and cost, and improve accessibility and test reproducibility, thereby enabling healthcare systems to run more efficiently and offer patients more timely results. Ideally, such a platform should incorporate a measure of the underlying tumor biology to provide a fully explainable, white box solution, and may offer further insights into the identification of early recurrence events. Aims The aim of this study was to establish whether our computer-aided solution’s (Q-Plasia OncoReader Breast, QPORB) digital biomarker representing G1/S cell cycle deformations extracted from H&amp;E WSIs was prognostic for disease-free survival (DFS) and could predict disease recurrence, particularly in the setting of low risk ODXRS breast cancers. Methods Primary breast cancer resection/excision specimens (n=70 cases) sent for ODXRS testing from St James’s University Hospital, UK (2016-2019) were collected. Anonymised diagnostic glass slides (n=198 slides) of H&amp;E-stained tumors were scanned at x20 magnification on an Aperio AT2 scanner. In parallel, relevant clinical and histological data were collected from pathology reports and electronic patient records, including both ODXRS and recurrence events during follow-up. The QPORB recurrence scale (QPORB-RS), which combines statistical physics and tumor biology to identify image-based malignant cell cycle deformation, extracts prognostic information from WSIs. The contribution of potential confounders (age, stage, grade, lesion size, Nottingham prognostic index and Charlson score) were accounted for. Results The QPORB-RS was prognostic for DFS for patients with predominantly node-negative (including node micro-metastases) HR+/HER2- tumors over a median follow-up period of 5 years (P=0.02; dichotomized Kaplan Meyer with median cut-off). The QPORB-RS concurred with ODXRS’s high vs. low recurrence risk in 73% (19/26) and 61% (27/44) of cases, respectively, with an overall agreement of 66% (46/70). Moreover, the QPORB-RS identified all 5 patients who had recurrences (with ODXRS of 6, 9, 10, 21 and 26, and ages of 55, 66, 42, 35 and 50 years, respectively) as being high risk in the subset of those given a low (including historically intermediate) ODXRS and who did not receive chemotherapy. Conclusion The QPORB-RS is a good prognostic test of risk of disease recurrence in breast cancer patients with predominantly node-negative (including node micro-metastases) HR+/HER2- tumors within a median 5-year follow-up period. Our efforts are now focussed on extending this cohort and establishing the prognostic value of the QPORB-RS across all breast carcinomas, regardless of molecular subtype, stage/node positivity and menopausal status. Citation Format: Satabhisa Mukhopadhyay, Tathagata Dasgupta, Elizabeth Walsh, Rebecca Millican-Slater, Andrew hanby, Joanne Stephenson, Craig A. Bunnell, Nicolas M. Orsi. Prediction of disease recurrence in low risk Oncotype Dx breast cancers from digital H&amp;E-stained whole slide images of pre-treatment resections alone [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-05-48.

The ability of magnetic resonance imaging to predict lymph node metastases and the risk of recurrence in rectal cancer.

This study aimed to examine the diagnostic accuracy and prognostic value of magnetic resonance imaging (MRI) detected lymph nodes in rectal cancer. We evaluated 806 rectal cancer patients consecutively operated on between 2015 and 2018 at Helsinki University Hospital. In total, 485 patients met the inclusion criteria of presenting with stage I-III disease and were intended for curative treatment at the time of diagnosis. The effect of MRI-detected clinical lymph node status (cN) on cumulative overall survival (OS), disease-specific survival (DSS) and disease-free survival (DFS) was calculated using the Kaplan-Meier analysis. Negative predictive value (NPV) of MRI-lymphnode negativity was 74.8%. Positive predictive value of lymph node metastasis was only 48.6%. In the Kaplan-Meier survival analysis, OS (p = 0.989), DSS (p = 0.911), and DFS (p = 0.109) did not significantly differ according to MRI nodal status. However, cumulative disease-free survival significantly (p < 0.001) differed according to the histopathological lymph node metastasis status (pN). MRI detected lymph node positivity appears insufficiently precise and cannot predict disease recurrence or survival. Therefore, it should not serve as an independent risk factor when considering neoadjuvant treatment options for rectal cancer patients.

Ultrasensitive immunosensor for monitoring of CA 19-9 pancreatic cancer marker using electrolyte-gated TiS3 nanoribbons field-effect transistor

Measuring CA 19-9 antigen level is critical for early diagnosis of pancreatic cancer, monitoring the treatment process, and predicting disease recurrence. The purpose of this research is to assess the application of novel few-layered TiS3 nanoribbons material as a channel material in electrolyte-gated field-effect transistor immunosensor for rapid detection of CA 19-9 antigen as a cancer marker. Accordingly, TiS3 nanoribbons were produced through liquid-phase exfoliation of as-synthesized TiS3 whiskers in N, N-dimethylformamide. Then, dispersed TiS3 nanoribbons were drop cast onto the FET surface to form an active channel material between source and drain electrodes. Subsequently, the channel surface was modified by utilizing 1-naphthylamine (NA) and glutaraldehyde (GA) to strengthen the binding of monoclonal antibody 19-9 to TiS3 nanoribbons. Spectroscopic and microscopic methods were utilized for comprehensive characterizations. Electrical characterization of electrolyte-gated TiS3 nanoribbons field-effect transistor represented a depletion-mode n-type behavior with field-effect mobility of 0.059 cm2/Vs, current on/off ratio of 10.88 and subthreshold swing (SS) of 450.9 mV/decade. With increasing in CA 19-9 antigen concentration from 1.0 × 10−12 U/mL to 1.0 × 10−5 U/mL, a decrease in the drain current occurred with high sensitivity of 0.04 μA/decade and a detection limit of 1.3 × 10−13 U/mL. Additionally, the proposed TiS3 nanoribbons FET immunosensor exhibited outstanding selectivity, and its good performance was compared with an enzyme-linked immunosorbent assay (ELISA) for spiked real human serum samples. The good and satisfactory obtained results of the proposed immunosensor suggest that the developed platform can be a superb candidate for cancer diagnosis and therapeutic monitoring.

Patient-specific tumor-informed circulating tumor DNA (ctDNA) assay to predict cancer recurrence in patients with resected pancreatic cancer.

744 Background: Pancreatic cancer (PC) is one of the leading causes of cancer death. Identifying molecular residual disease (MRD) with tailored tumor-informed ctDNA-based next-generation sequencing (NGS) assays after curative surgery could facilitate the individualized management of patients with resected pancreatic cancer (PC). Here, we prospectively evaluated the clinical performance of tumor-informed ctDNA mutation analysis using a novel Burning Rock Patient Specific Prognostic and Potential Therapeutic Marker Tracking (brPROPHET) approach for assessing MRD in patients with resected PC. Methods: The prospective cohort study recruited patients (n = 20) diagnosed with resectable stage I-III PC. Plasma samples (n = 63) were collected before surgery (baseline), 7-days after surgery (landmark), 30-days after surgery (before any adjuvant therapy), during the adjuvant therapy and follow-up. Individual tumors and matched white blood cells (WBCs) were whole-exome sequenced and somatic mutations were identified. Serial plasma samples were analyzed by a personalized, tumor-informed ctDNA-based NGS assay (brPROPHET) designed to target up to 50 variants per patient. Results: A total of 20 patients (stage I/II 10 [50%]/9[ 45%]) were analyzed. Patients were followed for a median of 190 days (range: 158 days to 396 days). Preoperative ctDNA was detected in 100% (20/20) of the patients. MRD status was analyzed postoperatively on day 7 and day 30 with a positivity rate of 11% (2/18) and 17% (2/12), respectively. Of the 4 patients with known recurrences, 2 had detectable ctDNA (50%, 2/4) at 7 days after surgery, whereas all disease-free patients were ctDNA-negative (100%, 13/13) at this time point. Detection at the landmark timepoint 7 days after surgery was associated with shorter recurrence-free survival (hazard ratio [HR]: 16.87, p=0.00363). The landmark negative predictive value (NPV) and positive predictive value (PPV) were 87.5% and 100%, respectively. When integrating all timepoints, 100% (4/4) of relapse patients were ctDNA positive before relapse, with the median leading time by brPROPHET assay to radiological recurrence was 126 days, whereas all of the patients with constant ctDNA negative status were disease-free (longitudinal PPV 80%, NPV 100%). In one relapsed patient who had elevated preoperative carbohydrate antigen (CA) 19-9 and constant normal postoperative CA19-9 (&lt;27 U/ml), ctDNA was detected prior to radiological relapse, with a lead time of 211 days. Conclusions: Patient-specific tumor-informed ctDNA-based postoperative monitoring predicts disease recurrence at earlier postoperative settings better than the clinical parameter CA19-9, which paves an alternative strategy in the individualized management of patients with resected PC.

Early MRD predicts disease recurrence and benefit from adjuvant chemotherapy in CRC.

Early MRD predicts disease recurrence and benefit from adjuvant chemotherapy in CRC.

MR imaging phenotypes and features associated with pathogenic mutation to predict recurrence or metastasis in breast cancer

ObjectivesDistant metastasis remains the main cause of death in breast cancer. Breast cancer risk is strongly influenced by pathogenic mutation.This study was designed to develop a multiple-feature model using clinicopathological and imaging characteristics adding pathogenic mutations associated signs to predict recurrence or metastasis in breast cancers in high familial risk women.MethodsGenetic testing for breast-related gene mutations was performed in 54 patients with breast cancers. Breast MRI findings were retrospectively evaluated in 64 tumors of the 54 patients. The relationship between pathogenic mutation, clinicopathological and radiologic features was examined. The disease recurrence or metastasis were estimated. Multiple logistic regression analyses were performed to identify independent factors of pathogenic mutation and disease recurrence or metastasis. Based on significant factors from the regression models, a multivariate logistic regression was adopted to establish two models for predicting disease recurrence or metastasis in breast cancer using R software.ResultsOf the 64 tumors in 54 patients, 17 tumors had pathogenic mutations and 47 tumors had no pathogenic mutations. The clinicopathogenic and imaging features associated with pathogenic mutation included six signs: biologic features (p = 0.000), nuclear grade (p = 0.045), breast density (p = 0.005), MRI lesion type (p = 0.000), internal enhancement pattern (p = 0.004), and spiculated margin (p = 0.049). Necrosis within the tumors was the only feature associated with increased disease recurrence or metastasis (p = 0.006). The developed modelIincluding clinico-pathologic and imaging factors showed good discrimination in predicting disease recurrence or metastasis. Comprehensive model II, which included parts of modelIand pathogenic mutations significantly associated signs, showed significantly more sensitivity and specificity for predicting disease recurrence or metastasis compared to Model I.ConclusionsThe incorporation of pathogenic mutations associated imaging and clinicopathological parameters significantly improved the sensitivity and specificity in predicting disease recurrence or metastasis. The constructed multi-feature fusion model may guide the implementation of prophylactic treatment for breast cancers at high familial risk women.

Tumor-informed or tumor-agnostic circulating tumor DNA as a biomarker for risk of recurrence in resected colorectal cancer patients.

Circulating tumor DNA (ctDNA) has been increasingly recognized as a promising minimally-invasive biomarker that could identify patients with minimal residual disease and a high risk of recurrence after definitive treatment. In this study, we've compared the clinical utility and sensitivity of 2 different approaches to ctDNA analyses: tumor-informed and tumor-agnostic in the management of colorectal (CRC) patients. The clinical benefits of a single timepoint ctDNA analysis compared to serial ctDNA monitoring after definitive treatment were also evaluated to uncover the ideal surveillance protocol. Patient-paired resected tumor tissues, peripheral blood cells, and a total of 127 pre-operative and serial plasma cell-free DNA (cfDNA) samples after definitive treatment from 38 CRC patients that had undergone curative intent surgery were analyzed using a commercial NGS cfDNA panel. Up to 84% (32/38) of the recruited patients were detected with at least 1 genomic alteration from the tumor tissues that could be monitored using the tumor-informed ctDNA approach and none of the detected alterations were clonal hematopoiesis (CH) related. In contrast, 37% (14/38) of patients were detected with at least 1 monitoring alteration after exclusion of CH mutations using the tumor-agnostic approach. Serial plasma samples after definitive therapy were available for 31 patients. In the landmark ctDNA analysis, 24% (7/29) of patients had detectable ctDNA and were more likely to relapse than ctDNA-negative patients (p < 0.05). The landmark analysis sensitivity and specificity for recurrence were 67% and 87%, respectively. The incorporation of longitudinal ctDNA analysis at 6-months intervals improved the sensitivity to 100%. The median variant allele frequency (VAF) of the ctDNA mutations detected during surveillance was 0.028% (range: 0.018-0.783), where up to 80% (8/10) of the mutations were detected at VAF lower than the tumor-agnostic detection limit of 0.1%. Utilizing the tumor-agnostic approach reduced the recurrence detection sensitivity to 67% (4/6). Serial ctDNA analyses predicted disease recurrence at a median of 5 months ahead of radiological imaging. Longitudinal monitoring using tumor-informed ctDNA testing shows high analytical sensitivity, low probability of false-positive results due to CH mutations, and improved sensitivity in detecting recurrence which may modify the clinical management of CRC.

Major pathologic response exhibited distinct prognostic significance for lung adenocarcinoma post different modalities of neoadjuvant therapy.

For non-small cell lung cancer (NSCLC) patients receiving neoadjuvant therapy, the major pathologic response (MPR) is defined as the percentage of residual viable tumor cells (%RVT) in the tumor bed of no more than 10%. It has been proposed as a predictor of survival in neoadjuvant therapy-treated cohorts. Nonetheless, the significance of %RVT in the pathological assessment of lung adenocarcinoma cohorts remains undetermined. Overall, 152 lung adenocarcinoma patients were included in this retrospective study, among whom 67 received neoadjuvant targeted therapy and 85 received neoadjuvant chemotherapy. Clinicopathological characteristics, neoadjuvant treatment response, and survival status were investigated. The routinely adopted standard for MPR (%RVT ≤10%) failed to differentiate prognosis in the lung adenocarcinoma population. For the neoadjuvant chemotherapy cohort, the optimal %RVT cutoff value of RFS was 60%. However, this cutoff value was clinically insignificant in the neoadjuvant targeted therapy cohort. Hence, for these patients, we built a nomogram model including high-grade patterns and ypN stage to predict disease recurrence, demonstrating a high efficacy (a bootstrap-corrected C-index of 0.731). %RVT served as a strong indicator of the prognosis of lung adenocarcinoma in patients receiving neoadjuvant chemotherapy but not neoadjuvant targeted therapy. Residual high-grade pathological patterns might substitute MPR in prognostic evaluation of lung adenocarcinoma post-targeted therapy.

Plasma metabolomics, lipidomics and cytokinomics profiling predict disease recurrence in metastatic colorectal cancer patients undergoing liver resection.

In metastatic colorectal cancer (mCRC) patients (pts), treatment strategies integrating liver resection with induction chemotherapy offer better 5-year survival rates than chemotherapy alone. However, liver resection is a complex and costly procedure, and recurrence occurs in almost 2/3rds of pts, suggesting the need to identify those at higher risk. The aim of this work was to evaluate whether the integration of plasma metabolomics and lipidomics combined with the multiplex analysis of a large panel of plasma cytokines can be used to predict the risk of relapse and other patient outcomes after liver surgery, beyond or in combination with clinical morphovolumetric criteria. Peripheral blood metabolomics and lipidomics were performed by 600 MHz NMR spectroscopy on plasma from 30 unresectable mCRC pts treated with bevacizumab plus oxaliplatin-based regimens within the Obelics trial (NCT01718873) and subdivided into responder (R) and non-R (NR) according to 1-year disease-free survival (DFS): ≥ 1-year (R, n = 12) and < 1-year (NR, n = 18). A large panel of cytokines, chemokines, and growth factors was evaluated on the same plasma using Luminex xMAP-based multiplex bead-based immunoassay technology. A multiple biomarkers model was built using a support vector machine (SVM) classifier. Sparse partial least squares discriminant analysis (sPLS-DA) and loading plots obtained by analyzing metabolomics profiles of samples collected at the time of response evaluation when resectability was established showed significantly different levels of metabolites between the two groups. Two metabolites, 3-hydroxybutyrate and histidine, significantly predicted DFS and overall survival. Lipidomics analysis confirmed clear differences between the R and NR pts, indicating a statistically significant increase in lipids (cholesterol, triglycerides and phospholipids) in NR pts, reflecting a nonspecific inflammatory response. Indeed, a significant increase in proinflammatory cytokines was demonstrated in NR pts plasma. Finally, a multiple biomarkers model based on the combination of presurgery plasma levels of 3-hydroxybutyrate, cholesterol, phospholipids, triglycerides and IL-6 was able to correctly classify patients by their DFS with good accuracy. Overall, this exploratory study suggests the potential of these combined biomarker approaches to predict outcomes in mCRC patients who are candidates for liver metastasis resection after induction treatment for defining personalized management and treatment strategies.

Unicystic ameloblastoma: A retrospective study on recurrent factors from a single institute database.

Unicystic ameloblastomas are a variant of ameloblastoma with a definite recurrence rate because of the biological behaviours of the tumour. The risk factors associated with disease recurrence were analysed in this retrospective study. A total of 132 patients with primary unicystic ameloblastoma reported in a tertiary hospital from 2005 to 2015 were analysed to identify the clinic-pathological and radiological factors associated with recurrence using univariate and multivariate Cox regression analyses. The mean volume was 30.54cm3± 12.55 cm3, and this value differed significantly according to recurrence (p < 0.001). Root resorption and bone cortex/soft tissue invasion were also significantly associated with recurrence among unicystic ameloblastoma patients (p=0.017 vs. p < 0.001, respectively). A new stage classification system was developed to predict disease recurrence of patients. The multivariate Cox regression analysis revealed that the new stage classification system was the only predictor of disease recurrence in unicystic ameloblastoma patients (p < 0.001), regardless of root resorption, position and site characteristics. Volume, root resorption and bone cortex/soft tissue invasion were risk factors for disease recurrence among unicystic ameloblastoma patients. The new stage classification was an independent predictor of disease recurrence in patients with unicystic ameloblastoma.