Clinical Trials Of Adjuvant Therapy Research Articles

Predictors of disease recurrence in high-risk non-metastatic renal cell carcinoma patients post-surgical resection A single-center, retrospective study.

Approximately 20-40% of kidney cancer patients treated for localized disease experience post-surgical recurrence. Several prognostic models exist to help clinicians determine the risk of distant recurrence, but these models vary in criteria and endpoints. We aimed to examine the recurrence rate and clinicopathologic factors as predictors of recurrence in high-risk renal cell carcinoma (RCC) patients. We conducted a single-center, retrospective chart review of pT3 RCC patients who underwent a nephrectomy between January 2000 and December 2015. Patients registered in clinical trials for adjuvant therapy and those with fewer than three years of followup were excluded. Kaplan-Meier survival analysis and univariate and multivariate Cox regression were performed to identify the rate and predictors of disease recurrence. Eighty-eight pT3 RCC patients were included, and 39 patients had recurrence with a median of 23.5 months (range 1.6-127.5). Nine patients had disease recurrence beyond 58 months. Kaplan-Meier log-rank tests identified patients with negative surgical margins and low Fuhrman nuclear grades had greater recurrence-free survival. Univariate Cox regression revealed positive surgical margins, high Fuhrman nuclear grade, and large tumor sizes were significant predictors. In the multivariate Cox regression model, high Fuhrman nuclear grade and positive surgical margins were significant predictors of recurrence. Disease recurrence occurred in 44% of pT3-staged patients. High Fuhrman nuclear grade and positive surgical margins were associated with time to recurrence. Physicians should use prognostic models to facilitate conversations about disease recurrence and continue to monitor high-risk patients beyond the recommended five-year followup period. We recommend monitoring pT3 resected patients for up to 10 years post-surgery.

Interferon-expressing oncolytic adenovirus + chemoradiation inhibited pancreatic cancer growth in a hamster model.

Past clinical trials of adjuvant therapy combined with interferon (IFN) alpha, fluorouracil, cisplatin, and radiation improved the 5-year survival rate of pancreatic ductal adenocarcinoma (PDAC). However, these trials also revealed the disadvantages of the systemic toxicity of IFN and insufficient delivery of IFN. To improve efficacy and tolerability, we have developed an oncolytic adenovirus-expressing IFN (IFN-OAd). Here, we evaluated IFN-OAd in combination with chemotherapy (gemcitabine + nab-paclitaxel) + radiation. Combination index (CI) analysis showed that IFN-OAd + chemotherapy + radiation was synergistic (CI <1). Notably, IFN-OAd + chemotherapy + radiation remarkably suppressed tumor growth and induced a higher number of tumor-infiltrating lymphocytes without severe side toxic effects in an immunocompetent and adenovirus replication-permissive hamster PDAC model. This is the first study to report that gemcitabine + nab-paclitaxel, the current first-line chemotherapy for PDAC, did not hamper virus replication in a replication-permissive immunocompetent model. IFN-OAd has the potential to overcome the barriers to clinical application of IFN-based therapy through its tumor-specific expression of IFN, induction of antitumor immunity, and sensitization with chemoradiation. Combining IFN-OAd with gemcitabine + nab-paclitaxel + radiation might be an effective and clinically beneficial treatment for PDAC patients.

Cell Immunotherapy against Melanoma: Clinical Trials Review.

Melanoma is one of the most aggressive and therapy-resistant types of cancer, the incidence rate of which grows every year. However, conventional methods of chemo- and radiotherapy do not allow for completely removing neoplasm, resulting in local, regional, and distant relapses. In this case, adjuvant therapy can be used to reduce the risk of recurrence. One of the types of maintenance cancer therapy is cell-based immunotherapy, in which immune cells, such as T-cells, NKT-cells, B cells, NK cells, macrophages, and dendritic cells are used to recognize and mobilize the immune system to kill cancer cells. These cells can be isolated from the patient's peripheral blood or biopsy material and genetically modified, cultured ex vivo, following infusion back into the patient for powerful induction of an anti-tumor immune response. In this review, the advantages and problems of the most relevant methods of cell-based therapy and ongoing clinical trials of adjuvant therapy of melanoma are discussed.

Comparison of patients with high-risk nonmetastatic clear cell renal carcinoma in adjuvant therapy trials versus nonclinical trial patients.

361 Background: Characteristics of patients with high risk for recurrence non-metastatic renal cell carcinoma (nmRCC) participating in adjuvant therapy clinical trials post-nephrectomy have not been well described. We evaluated high risk nmRCC patients in the CKCis database to explore differences between trial and non-trial patients. Methods: Adult patients undergoing partial or radical nephrectomy for clear cell nmRCC between January 1, 2011 and March 31, 2021 were included. CKCis is a prospective cohort of patients from 14 Canadian academic institutions. Patients with high risk nmRCC (using modified UCLA Integrated Staging System) were included. Demographic, clinical, and survival statistics were analyzed for all patients and comparatively for the trial and non-trial groups. Results: 1459 patients, including 63 in adjuvant trials, were evaluated. 71% were male, 91% had pT3N0M0 disease. Disease characteristics including tumor size, stage, grade, location, necrosis, and margin status were similar between groups. Trial patients were younger (mean age 58.1 vs. 63.6; p &lt; 0.0001) and had lower Charlson Comorbidity Index scores (median 4 [3,6) vs. 5 [4,6] p &lt; 0.001). Estimated overall survival (OS) at 5 years was 80.8% (95% CI, 65,90) for trial patients and 74.8% (95% CI, 71,78.2) for non-trial patients. Recurrence-free survival at 5 years for trial patients was 48.6% (95% CI, 34,61.7) and 39.2% (95% CI, 35.2,43.1) for non-trial patients. Conclusions: Patients in adjuvant trials were younger and healthier at baseline than the average high risk nmRCC CKCis patient. Trial patients appear to have had longer time to recurrence and longer survival compared to non-trial patients, although not reaching statistical significance. Selection bias is common in clinical trials and evaluation of real-world population-based evidence of patients receiving adjuvant therapy will be important to ensure phase 3 trial results have external validity.

Uveal melanoma: laboratory advances and new frontiers in patient care.

To review recent advancements in the genetic understanding, diagnosis, prognosis, and treatment of uveal melanoma (UM). UM is a molecularly distinct melanocytic malignancy driven by mutations in GNAQ or GNA11, with mitogen-activated protein kinase pathway upregulation. Earlier diagnosis and treatment are important factors for improving life prognosis. These goals can be aided by more objective multimodal imaging risk factors for the prediction of malignant nevus transformation and novel treatment strategies such as customized radiation fields and nanoparticle therapy to reduce vision-threatening treatment side effects. The risk for metastatic disease can be reliably predicted through gene expression profiling or the Cancer Genome Atlas project classification, and combined use of clinical tumor features with molecular data allows for highly individualized patient prognosis. Patients with high-risk UM should be considered for clinical trials of adjuvant therapy to prevent metastatic disease. For patients with clinically evident metastasis, combination immunotherapy regimens, T cell-based therapies, and focal adhesion kinase inhibitors offer hope for improved clinical response rates. Improved understanding of UM molecular pathogenesis and clinical trials of targeted therapy for prevention and treatment of metastatic disease may improve patient survival for this challenging disease.

Automated digital TIL analysis (ADTA) adds prognostic value to standard assessment of depth and ulceration in primary melanoma

Accurate prognostic biomarkers in early-stage melanoma are urgently needed to stratify patients for clinical trials of adjuvant therapy. We applied a previously developed open source deep learning algorithm to detect tumor-infiltrating lymphocytes (TILs) in hematoxylin and eosin (H&E) images of early-stage melanomas. We tested whether automated digital (TIL) analysis (ADTA) improved accuracy of prediction of disease specific survival (DSS) based on current pathology standards. ADTA was applied to a training cohort (n = 80) and a cutoff value was defined based on a Receiver Operating Curve. ADTA was then applied to a validation cohort (n = 145) and the previously determined cutoff value was used to stratify high and low risk patients, as demonstrated by Kaplan–Meier analysis (p ≤ 0.001). Multivariable Cox proportional hazards analysis was performed using ADTA, depth, and ulceration as co-variables and showed that ADTA contributed to DSS prediction (HR: 4.18, CI 1.51–11.58, p = 0.006). ADTA provides an effective and attainable assessment of TILs and should be further evaluated in larger studies for inclusion in staging algorithms.

Brigham and Women's Hospital tumor classification system for basal cell carcinoma identifies patients with risk of metastasis and death

Despiteapproximately 4400 locally advanced US cases annually, high-stage basal cell carcinoma (BCC) is ill-defined. To develop a tumor (T) staging system for BCC that will predict metastasis/death and compare its performance with that of the American Joint Committee on Cancer 8th edition (AJCC8) T-staging system. Brigham and Women's Hospital (BWH) T staging was developed from a previously published nested cohort of 488 primary BCCs. Tumors were staged via BWH and AJCC8 T-staging systems, and predictions of metastasis and/or death were compared. The BWH and AJCC8 T-staging systems both captured all metastases/deaths in high T stages (BWH, T2; AJCC8, T3/T4). BWH T2 included 54% fewer cases ≥2cm than AJCC8 T3/T4. BWH had a higher specificity (0.92 vs 0.80; P<.001) and positive predictive value (24% vs 11%, P<.001) for identifying cases at risk for metastasis/death, and the C-statistic was superior for BWH (P<.001). The BWH T2 10-year cumulative incidence of metastasis/death was 37% (95% confidence interval, 21%-60%). Two-center cohort. BWH and AJCC 8 BCC staging both capture all metastases and deaths in the upper stages. However, BWH staging does so in half the number of cases, thus minimizing inappropriate up-staging. The risk of metastasis or death in BWH T2 BCC is sufficient to warrant surveillance for recurrence and clinical trials of adjuvant therapy.

A Genomic-Pathologic Annotated Risk Model to Predict Recurrence in Early-Stage Lung Adenocarcinoma

Recommendations for adjuvant therapy after surgical resection of lung adenocarcinoma (LUAD) are based solely on TNM classification but are agnostic to genomic and high-risk clinicopathologic factors. Creation of a prediction model that integrates tumor genomic and clinicopathologic factors may better identify patients at risk for recurrence. To identify tumor genomic factors independently associated with recurrence, even in the presence of aggressive, high-risk clinicopathologic variables, in patients with completely resected stages I to III LUAD, and to develop a computational machine-learning prediction model (PRecur) to determine whether the integration of genomic and clinicopathologic features could better predict risk of recurrence, compared with the TNM system. This prospective cohort study included 426 patients treated from January 1, 2008, to December 31, 2017, at a single large cancer center and selected in consecutive samples. Eligibility criteria included complete surgical resection of stages I to III LUAD, broad-panel next-generation sequencing data with matched clinicopathologic data, and no neoadjuvant therapy. External validation of the PRecur prediction model was performed using The Cancer Genome Atlas (TCGA). Data were analyzed from 2014 to 2018. The study end point consisted of relapse-free survival (RFS), estimated using the Kaplan-Meier approach. Associations among clinicopathologic factors, genomic alterations, and RFS were established using Cox proportional hazards regression. The PRecur prediction model integrated genomic and clinicopathologic factors using gradient-boosting survival regression for risk group generation and prediction of RFS. A concordance probability estimate (CPE) was used to assess the predictive ability of the PRecur model. Of the 426 patients included in the analysis (286 women [67%]; median age at surgery, 69 [interquartile range, 62-75] years), 318 (75%) had stage I cancer. Association analysis showed that alterations in SMARCA4 (clinicopathologic-adjusted hazard ratio [HR], 2.44; 95% CI, 1.03-5.77; P = .042) and TP53 (clinicopathologic-adjusted HR, 1.73; 95% CI, 1.09-2.73; P = .02) and the fraction of genome altered (clinicopathologic-adjusted HR, 1.03; 95% CI, 1.10-1.04; P = .005) were independently associated with RFS. The PRecur prediction model outperformed the TNM-based model (CPE, 0.73 vs 0.61; difference, 0.12 [95% CI, 0.05-0.19]; P < .001) for prediction of RFS. To validate the prediction model, PRecur was applied to the TCGA LUAD data set (n = 360), and a clear separation of risk groups was noted (log-rank statistic, 7.5; P = .02), confirming external validation. The findings suggest that integration of tumor genomics and clinicopathologic features improves risk stratification and prediction of recurrence after surgical resection of early-stage LUAD. Improved identification of patients at risk for recurrence could enrich and enhance accrual to adjuvant therapy clinical trials.

Abstract 5442: The Collaborative Ocular Oncology Group study number 2: A prospective multi-center evaluation of uveal melanoma prognostic biomarkers

Abstract Introduction: Uveal melanoma (UM) is a highly aggressive eye cancer that leads to metastatic death in up to half of patients. UM has a propensity to undergo early micrometastasis prior to treatment of the primary tumor, with later emergence of overt metastatic disease. UM can be stratified into Class 1 (low metastatic risk) and Class 2 (high metastatic risk) using a prospectively validated 12-gene expression profile (GEP) molecular prognostication classifier. The Collaborative Ocular Oncology Group Study 2 (COOG2) is being conducted to prospectively evaluate new prognostic biomarkers in UM, including expression of PRAME, and prognostic driver mutations in BAP1, SF3B1, and EIF1AX. Methods: The COOG2 is a 24 center, prospective study of UM patients undergoing prognostic testing using the CLIA-certified DecisionDx-UM test (Castle Biosciences, Inc) between July 2017 and December 2019. Molecular analysis is performed on residual clinical samples. Data collected include clinical annotations, patient outcomes, GEP, PRAME status, and mutations in BAP1, SF3B1, and EIF1AX. Results: To date, there are 1300 participants enrolled. The baseline characteristics are as follows: 52% male, and 48% female; 87% non-Hispanic, 3% Hispanic, and 10% unknown. GEP classification is 66% class 1 and 34% class 2. PRAME status is 68% PRAME (-) and 32% PRAME (+). Targeted sequencing has been performed on 650 samples and is being analyzed. Conclusions: The COOG2 will establish a new standard of prognostic testing accuracy from a single fine needle biopsy in UM. The resulting integrated prognostic testing platform will be used as a stratification tool for entry into clinical trials of adjuvant therapy in high-risk patients. Citation Format: Christina L. Decatur, Michael A. Durante, Zelia M. Correa, Thomas M. Aaberg, Prithvi Mruthyunjaya, Amy C. Schefler, J. William Harbour. The Collaborative Ocular Oncology Group study number 2: A prospective multi-center evaluation of uveal melanoma prognostic biomarkers [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5442.

Nomogram Predicting Bladder Cancer–specific Mortality After Neoadjuvant Chemotherapy and Radical Cystectomy for Muscle-invasive Bladder Cancer: Results of an International Consortium

Background: Cisplatin-based neoadjuvant chemotherapy (NAC) for muscle-invasive bladder cancer (MIBC) is associated with improved overall and cancer-specific survival. The post-NAC pathological stage has previously been reported to be a major determinant of outcome. Objective: To develop a postoperative nomogram for survival based on pathological and clinical parameters from an international consortium. Design, setting, and participants: Between 2000 and 2015, 1866 patients with MIBC were treated at 19 institutions in the USA, Canada, and Europe. Analysis was limited to 640 patients with adequate follow-up who had received three or more cycles of NAC. Outcome measurements and statistical analysis: A nomogram for bladder cancer–specific mortality (BCSM) was developed by multivariable Cox regression analysis. Decision curve analysis was used to assess the model’s clinical utility. Results and limitations: A total of 640 patients were identified. Downstaging to non-MIBC (ypT1, ypTa, and ypTis) occurred in 271 patients (42 %), and 113 (17 %) achieved a complete response (ypT0N0). The 5-yr BCSM was 47.2 % (95 % confidence interval [CI]: 41.2–52.6 %). On multivariable analysis, covariates with a statistically significant association with BCSM were lymph node metastasis (hazard ratio [HR] 1.90 [95% CI: 1.4–2.6]; p < 0.001), positive surgical margins (HR 2.01 [95 % CI: 1.3–2.9]; p < 0.001), and pathological stage (with ypT0/Tis/Ta/T1 as reference: ypT2 [HR 2.77 {95 % CI: 1.7–4.6}; p < 0.001] and ypT3–4 [HR 5.9 {95 % CI: 3.8–9.3}; p < 0.001]). The area under the curve of the model predicting 5-yr BCSM after cross validation with 300 bootstraps was 75.4 % (95 % CI: 68.1–82.6 %). Decision curve analyses showed a modest net benefit for the use of the BCSM nomogram in the current cohort compared with the use of American Joint Committee on Cancer staging alone. Limitations include the retrospective study design and the lack of central pathology. Conclusions: We have developed and internally validated a nomogram predicting BCSM after NAC and radical cystectomy for MIBC. The nomogram will be useful for patient counseling and in the identification of patients at high risk for BCSM suitable for enrollment in clinical trials of adjuvant therapy. Patient summary: In this report, we looked at the outcomes of patients with muscle-invasive bladder cancer in a large multi-institutional population. We found that we can accurately predict death after radical surgical treatment in patients treated with chemotherapy before surgery. We conclude that the pathological report provides key factors for determining survival probability.

A23 A Genomically Adjusted Clinicopathologic Model Predicts Recurrence in Resected Early-Stage Lung Squamous Cell Carcinoma

In contrast to lung adenocarcinoma, identification of clinically relevant genomic perturbations in lung squamous cell carcinoma (LUSC) remains poorly characterized. Prognostic and therapeutic decisions following surgery in early and locoregionally advanced LUSC are almost exclusively driven by the TNM classification system, omitting high-risk clinicopathologic and tumor genomic information. To address this knowledge gap, we sought to determine if a combined clinicopathologic and genomic model could predict disease-free survival (DFS) better than traditional TNM assessments in completely resected LUSC. A retrospective cohort study of a prospectively maintained database was performed for patients (N=95) with pathologic stage I-III LUSC who underwent complete resection from 2008-2018. Patients who received any induction therapy (N=9) were excluded. All patients had complete clinicopathologic data with broad-panel next-generation sequencing of the primary tumor, including matched controls to bioinformatically filter germline variants. DFS, the primary endpoint, and overall survival (OS) were estimated using Kaplan-Meier. Genomic pathway alterations (N=10) were determined as we previously reported. The prognostic model established associations between high-risk clinicopathologic variables and genomic alterations with DFS through Cox regression models. Concordance probability estimate (CPE) was used to discriminate performance between the existing TNM model and the developed prediction models. The median age was 70 years (range, 55-84), one-third were female (n=35), 55% (N=52) were pathologic stage I, and 98% (N=93) were ever-smokers. Median follow-up was 2 years. Recurrence occurred in 20% (19/95) and DFS was 74% (95% CI, 84-96%) at two years. Clinicopathologic features associated with DFS were lymphovascular invasion, visceral-pleural invasion, and pathologic stage. Tumor genomic analysis revealed alterations in the transcription factor BCL6 were independently associated with worse DFS (HR 5.23, 95% CI 1.73, 15.9, p=0.009), while mutations in the tumor suppressor ARID1A were associated with a worse OS (HR 2.98, 95% CI 0.91, 9.77, p=0.07). Pathway-centric analyses revealed no associations with our primary or secondary endpoints. Our prognostic clinicopathologic model outperformed the internally validated TNM model (CPE, 0.74 vs. 0.70) for prediction of DFS and our clinicopathologic model, adjusted for BCL6 genomic alterations, further improved discrimination (CPE=0.77). We show that integration of high-risk clinicopathologic and tumor genomic profiling better predicts DFS than TNM classification alone in early-stage, surgically resected LUSC – an observation that may facilitate enrichment in future adjuvant therapy clinical trials. This exploratory genomic analysis also suggests future studies investigate putative therapeutic vulnerabilities in LUSC tumors harboring BCL6 and ARD1A genomic alterations.

The IASLC Lung Cancer Staging Project: Analysis of Resection Margin Status and Proposals for Residual Tumor Descriptors for Non-Small Cell Lung Cancer.

Our aim was to validate the prognostic relevance in NSCLC of potential residual tumor (R) descriptors, including the proposed International Association for the Study of Lung Cancer definition for uncertain resection, referred to as R(un). A total of 14,712 patients undergoing resection with full R status and survival were analyzed. The following were also evaluated: whether fewer than three N2 stations were explored, lobe-specific nodal dissection, extracapsular extension, highest lymph node station status, carcinoma in situ at the bronchial resection margin, and pleural lavage cytologic examination result. Revised categories of R0, R(un), R1, and R2 were tested for survival impact. In all, 14,293 cases were R0, 263 were R1, and 156 were R2 (median survivals not reached, 33 months, and 29 months, respectively). R status correlated with T and N categories. A total of 9290 cases (63%) had three or more N2 stations explored and 6641 cases (45%) had lobe-specific nodal dissection, correlated with increasing pN2. Extracapsular extension was present in 62 of 364 cases with available data (17%). The highest station was positive in 942 cases (6.4%). The pleural lavage cytologic examination result was positive in 59 of 1705 cases (3.5%): 13 had carcinoma in situ at the bronchial resection margin. After reassignment because of inadequate nodal staging in 56% of cases, 6070 cases were R0, 8185 were R(un), 301 were R1, and 156 were R2. In node-positive cases, the median survival times were 70, 50, and 30 months for R0, R(un) (p< 0.0001), and R1 (p < 0.001), respectively, with no significant difference between R0 and R(un) in pN0 cases. R descriptors have prognostic relevance, with R(un) survival stratifying between R0 and R1. Therefore, a detailed evaluation of R factor is of particular importance in the design and analyses of clinical trials of adjuvant therapies.

Validation of Melanoma Immune Profile (MIP), a Prognostic Immune Gene Prediction Score for Stage II-III Melanoma.

Biomarkers are needed to stratify patients with stage II-III melanoma for clinical trials of adjuvant therapy because, while immunotherapy is protective, it also confers the risk of severe toxicity. We previously defined and validated a 53-immune gene melanoma immune profile (MIP) predictive both of distant metastatic recurrence and of disease-specific survival (DSS). Here, we test MIP on a third independent population. A retrospective cohort of 78 patients with stage II-III primary melanoma was analyzed using the NanoString assay to measure expression of 53 target genes, and MIP score was calculated. Statistical analysis correlating MIP with DSS, overall survival, distant metastatic recurrence, and distant metastasis-free interval was performed using ROC curves, Kaplan-Meier curves, and standard univariable and multivariable Cox proportional hazards models. MIP significantly distinguished patients with distant metastatic recurrence from those without distant metastatic recurrence using ROC curve analysis (AUC = 0.695; P = 0.008). We defined high- and low-risk groups based on the cutoff defined by this ROC curve and find that MIP correlates with both DSS and overall survival by ROC curve analysis (AUC = 0.719; P = 0.004 and AUC = 0.698; P = 0.004, respectively). Univariable Cox regression reveals that a high-risk MIP score correlates with DSS (P = 0.015; HR = 3.2). MIP identifies patients with low risk of death from melanoma and may constitute a clinical tool to stratify patients with stage II-III melanoma for enrollment in clinical trials.

Abstract P3-01-01: Circulating tumor cells (CTCs) after neoadjuvant chemotherapy for triple negative breast cancer (TNBC)

Abstract Background: ARTEMIS (A Randomized, TNBC Enrolling trial to confirm Molecular profiling Improves Survival) is a randomized trial to determine if precision guided neoadjuvant chemotherapy (NAC) impacts rates of pathologic complete response in the breast and axillary nodes (pCR). We hypothesized that CTCs in peripheral blood after completion of NAC would provide prognostic information beyond pCR alone in TNBC patients. Methods: Blood was assessed for CTCs after NAC as part of two IRB approved studies, ARTEMIS (2014 – 0185/PA15-1050), and LAB04-0698. CTCs were identified using the Cell Search® System (Menarini Silicon Biosystems). Samples with one or more cells, also having morphologic criteria for malignancy, were deemed CTC positive. Log-rank test and Cox regression analysis were applied to evaluate associations between CTC positive, pCR, and overall survival. Results: pCR was achieved in 24/68 (35%) patients with TNBC. Twenty four patients (35%) were CTC positive. Three year overall survival was evaluated in 4 groups of patients: pCR and no CTCs (n=20), pCR and CTC positive (n=4), non-pCR and no CTCs (n=24) and non-pCR and CTC positive (n=20). Three year overall survival was higher in the pCR and no CTCs cohort (100%), compared to pCR and CTC positive (50%), non-pCR and no CTCs (83%), non-pCR and CTC positive (19%); log rank p&amp;lt;0.0001. In the non-pCR and CTC positive patient cohorts, the presence of CTCs was associated with significant risk of death at 3 years [hazard ratio of 12.3 (95% CI 3.4-454, p=0.00002)], whereas a favorable, but non-significant trend was noted for pCR [hazard ratio of 0.2 (95% CI 0.0, 1.4, p=0.11)]. Conclusion: The identification of CTCs after NAC has prognostic significance beyond that of pCR, and should be considered in evaluation of patients for clinical trials of adjuvant therapies. Citation Format: Lucci A, Hall C, Hess K, Ravenberg E, Clayborn A, Mittendorf E, Rauch G, Candelaria R, Moulder S, Thompson A. Circulating tumor cells (CTCs) after neoadjuvant chemotherapy for triple negative breast cancer (TNBC) [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-01-01.

Identification of seven long noncoding RNAs signature for prediction of biochemical recurrence in prostate cancer.

Accumulating evidence suggested that long noncoding RNAs (lncRNAs) possess a potential role in prostate cancer (PCa) diagnosis and prognosis. Rapid biochemical recurrence (BCR) is considered as a sign for clinical recurrence metastasis and PCa-specific mortality. Hence, the aim of the present study was to identify a lncRNA signature that can predict BCR of PCa accurately. Bioinformatics analysis, Kaplan–Meier analyses, Cox regression analyses, and Gene Set Enrichment Analysis (GSEA) were performed in a publicly available database with 499 PCa tissues and 52 matched normal tissues. A signature was identified. All these lncRNAs were differentially expressed between tumor and normal tissues and differentially expressed between high Gleason score and low Gleason score tissues. Furthermore, we developed a seven lncRNAs signature that can predict PCa BCR. Patients classified into low-risk group showed better BCR survival significantly than the patients in the high-risk group (hazard ratio = 0.32, 95% CI: 0.20–0.52, concordance index = 0.63). The area under the curve was 0.68 for BCR. The signature also had good discrimination for BCR in men with Gleason 7 PCa. In conclusion, our results suggest that the seven lncRNAs signature is a new biomarker of BCR and high risk in PCa. In addition, the individual lncRNA warrants further study to uncover the associated mechanisms of PCa progression and the signature could be used to design direct clinical trials for adjuvant therapy.

Development and external validation of a pathological nodal staging score for patients with clear cell renal cell carcinoma.

To develop and externally validate a model that quantifies the likelihood that a pathologically node-negative patient with clear cell renal cell carcinoma (cRCC) has, indeed, no lymph node metastasis (LNM). Data from 1389 patients treated with radical nephrectomy (RN) and lymph node dissection (LND) were analyzed. For external validation, we used data from 2270 patients in the Surveillance, Epidemiology and End Results (SEER) database. We estimated the sensitivity of pathologic nodal staging using a beta-binomial model and developed a pathological nodal staging score (pNSS), which represents the probability that a patient is correctly staged as node negative as a function of the number of examined lymph nodes (LNs). The mean and median number of LNs removed were 7.0 and 5.0 (standard deviation, SD 6.6; interquartile range, IQR 7.0) in the development cohort and 5.6 and 2.0 (SD 8.6, IQR 5.0) in the validation cohort, respectively. The probability of missing a positive LN decreased with increasing number of LNs examined. In both the validation and the development cohort, the number of LNs needed for correctly staging a patient as node negative increased with higher pathological tumor stage and Fuhrman grade. The number of examined LNs needed for adequate nodal staging in cRCC depends on pathological tumor stage and Fuhrman grade. We developed here and then externally validated a pNSS, which could help to refine patient counseling, decision-making regarding risk-stratified surveillance regimens and inclusion criteria for clinical trials of adjuvant therapy.

Analysis of Plasma Epstein-Barr Virus DNA in Nasopharyngeal Cancer After Chemoradiation to Identify High-Risk Patients for Adjuvant Chemotherapy: A Randomized Controlled Trial.

Purpose The contribution of adjuvant chemotherapy after chemoradiation therapy (CRT) in nasopharyngeal cancer (NPC) remains controversial. Plasma Epstein-Barr virus (EBV) DNA is a potential biomarker of subclinical residual disease in NPC. In this prospective, multicenter, randomized controlled trial, we used plasma EBV DNA to identify patients with NPC at a higher risk of relapse for adjuvant chemotherapy. Patients and Methods Eligible patients with histologically confirmed NPC of Union for International Cancer Control stage IIB to IVB, adequate organ function, and no locoregional disease or distant metastasis were screened by plasma EBV DNA at 6 to 8 weeks after radiotherapy (RT). Patients with undetectable plasma EBV DNA underwent standard surveillance. Patients with detectable plasma EBV DNA were randomly assigned to either adjuvant chemotherapy with cisplatin and gemcitabine for six cycles (arm 1) or observation (arm 2). Patients were stratified for primary treatment (RT v CRT) and stage (II/III v IV). The primary end point was relapse-free survival (RFS). Results Seven hundred eighty-nine patients underwent EBV DNA screening. Plasma EBV DNA was undetectable in 573 (72.6%) and detectable in 216 (27.4%); 104 (13.2%) with detectable EBV DNA were randomly assigned to arms 1 (n = 52) and 2 (n = 52). After a median follow-up of 6.6 years, no significant difference was found in 5-year RFS rate between arms 1 and 2 (49.3% v 54.7%; P = .75; hazard ratio for relapse or death, 1.09; 95% CI, 0.63 to 1.89). The level of post-RT plasma EBV DNA correlated significantly with the hazards of locoregional failure, distant metastasis, and death. Conclusion In patients with NPC with detectable post-RT plasma EBV DNA, adjuvant chemotherapy with cisplatin and gemcitabine did not improve RFS. Post-RT plasma EBV DNA level should be incorporated as the selection factor in future clinical trials of adjuvant therapy in NPC.

Defining individual recurrence risk following surgery for high risk non-metastatic renal cell carcinoma.

664 Background: Current models to estimate renal cell carcinoma (RCC) recurrence risk following surgery are derived from populations containing primarily low-risk patients. The objective of this study was to evaluate risk factors for recurrence among high risk non-metastatic RCC patients following attempted curative surgery. Methods: Data from 3 independent centers was analyzed for consecutive ≥ pT3a RCC patients without evidence of lymph node or distant metastases who were treated surgically from 2000-2016. Univariate and multivariate Cox proportional hazard models were used to evaluate associations of common clinical and pathological variables with recurrence risk. A risk model was constructed using independent predictors and recurrence risk was evaluated using Kaplan-Meier analysis. Results: Of 771 patients, 190 (24.6%) had RCC recurrence following attempted curative surgery at median 10.2 months (IQR 4.4-20.7). Median overall follow-up interval was 21.4 months (IQR 6.6-53.5). After multivariate Cox proportional hazard analysis, significant associations with RCC recurrence were not identified with: age, gender, race, systemic symptoms, local symptoms, pT stage, perinephric fat invasion, tumor thrombus, sinus fat invasion, serum hemoglobin, or serum albumin. Independent predictors included grade 4 HR 3.27 (95% CI 2.17, 4.92); tumor diameter &gt; 7cm HR 1.70 (95% CI 1.18, 2.45), tumor necrosis HR 1.47 (95% CI 1.06, 2.02), and sarcomatoid/ rhabdoid features HR 1.86 (95% CI 1.12, 3.09) An unweighted risk model was created by assigning one point for each independent predictor. Estimated 3-year recurrence risk was 14%, 25%, 40%, 49%, and 69% for patients with 0,1,2,3 and 4 risk factors (p &lt; 0.001) respectively. Conclusions: Independent predictors of recurrence for high risk non-metastatic RCC include: tumor diameter, necrosis, nuclear grade 4, and sarcomatoid/ rhabdoid features. This model may be used to estimate individual risk in RCC adjuvant therapy clinical trials.

Clinical Validity and Utility of Tumor-Infiltrating Lymphocytes in Routine Clinical Practice for Breast Cancer Patients: Current and Future Directions.

The interest in tumor-infiltrating lymphocytes (TILs) as a prognostic biomarker in breast cancer has grown in recent years. Biomarkers must undergo comprehensive evaluation in terms of analytical validity, clinical validity and clinical utility before they can be accepted as part of clinical practice. The International Immuno-Oncology Biomarker Working Group has developed a practice guideline on scoring TILs in breast cancer in order to standardize TIL assessment. The prognostic value of TILs as a biomarker in early-stage breast cancer has been established by assessing tumor samples in thousands of patients from large prospective clinical trials of adjuvant therapy. There is a strong linear relationship between increase in TILs and improved disease-free survival for triple-negative and HER2-positive disease. Higher levels of TILs have also been associated with increased rates of pathological complete response to neoadjuvant therapy. TILs have potential clinical utility in breast cancer in a number of areas. These include prediction of responders to immune checkpoint blockade, identification of primary HER2-positive and triple-negative patients who have excellent prognoses and may thus be appropriate for treatment de-escalation, and potentially incorporation into a neoadjuvant endpoint which may be a better surrogate maker for drug development.

A proposal of post-operative nomogram for overall survival in patients with renal cell carcinoma and venous tumor thrombus.

To identify the predictors of overall survival (OS) and create a post-operative prognostic model for patients with renal cell carcinoma (RCC) and venous tumor thrombus (VTT). The study cohort included patients with RCC and VTT that underwent full surgical resection between 2006 and 2016. Univariate and multivariate analyses were used to determine the prognostic factors of OS. A nomogram was developed and internally calibrated by bootstrap resampling method. A total of 185 patients were identified, including patients with thrombus present in the renal vein (109 patients, 58.9%), infrahepatic inferior vena cava (IVC; 68 patients, 36.8%), and suprahepatic IVC (8 patients, 4.3%). After a median follow-up of 30.2 months (interquartile range, 12.1-48.4 months), 63 (34.1%) patients died. Independent prognostic factors for OS included histological subtype, collecting system invasion, metastasis at surgery, De Ritis ratio (AST/ALT), and serum albumin. Independently predictive variables were used to create a nomogram, which achieved a concordance index of 0.75 for OS. For patients with RCC and VTT, the developed and internally validated post-operative nomogram can be used to select patients who may benefit from aggressive surveillance regimens or adjuvant therapy clinical trials.