Identification of a Novel Five-Gene Signature as a Prognostic and Diagnostic Biomarker in Colorectal Cancers

Colorectal cancer (CRC) is one of the leading causes of cancer-related mortality worldwide. The current TNM (Tumor, Node, and Metastasis) classification approach is suboptimal in determining the prognosis of CRC patients. The prognosis for CRC is affected by a variety of features that are present at the initial diagnosis. Herein, we performed a systematic exploration and established a novel five-panel gene signature as a prognostic and early diagnosis biomarker after performing differential gene expression analyses in five independent in silico CRCs cohort and independently validating it in one clinical cohort, using immunohistochemistry. Four genes (BDNF, PTGS2, GSK3B, and CTNNB1) were significantly upregulated and one gene (HPGD) was significantly downregulated in primary tumor tissues compared with adjacent normal tissues throughout all the five in silico datasets. The univariate CoxPH analysis yielded a five-gene signature that accurately predicted overall survival (OS) and recurrence-free survival (RFS) in the in silico training (AUC = 0.73 and 0.69, respectively) and one independent in silico validation cohort (AUC = 0.69 and 0.74, respectively). This five-gene signature demonstrated significant associations with poor OS in independent clinical validation cohorts of colon cancer (CC) patients (AUC = 0.82). Intriguingly, a risk stratification model comprising of the five-gene signature together with TNM stage and gender status achieved an even superior AUC of 0.89 in the clinical cohorts. On the other hand, the circulating mRNA expression of the upregulated four-gene signature achieved a robust AUC = 0.83 with high sensitivity and specificity as a diagnosis marker in plasma from CRC patients. We have identified a novel, five-gene signature as an independent predictor of OS, which in combination with TNM stage and gender offers an easy-to-translate and facile assay for the personalized risk-assessment in CRC patients.

Predicting the Extent of Resection of Motor-Eloquent Gliomas Based on TMS-Guided Fiber Tracking

Background: Surgical planning with nTMS-based tractography is proven to increase safety during surgery. A preoperative risk stratification model has been published based on the M1 infiltration, RMT ratio, and tumor to corticospinal tract distance (TTD). The correlation of TTD with corticospinal tract to resection cavity distance (TRD) and outcome is needed to further evaluate the validity of the model. Aim of the study: To use the postop MRI-derived resection cavity to measure how closely the resection cavity approximated the preoperatively calculated corticospinal tract (CST) and how this correlates with the risk model and the outcome. Methods: We included 183 patients who underwent nTMS-based DTI and surgical resection for presumed motor-eloquent gliomas. TTD, TRD, and motor outcome were recorded and tested for correlations. The intraoperative monitoring documentation was available for a subgroup of 48 patients, whose responses were correlated to TTD and TRD. Results: As expected, TTD and TRD showed a good correlation (Spearman’s ρ = 0.67, p < 0.001). Both the TTD and the TRD correlated significantly with the motor outcome at three months (Kendall’s Tau-b 0.24 for TTD, 0.31 for TRD, p < 0.001). Interestingly, the TTD and TRD correlated only slightly with residual tumor volume, and only after correction for outliers related to termination of resection due to intraoperative monitoring events or the proximity of other eloquent structures (TTD ρ = 0.32, p < 0.001; TRD ρ = 0.19, p = 0.01). This reflects the fact that intraoperative monitoring (IOM) phenomena do not always correlate with preoperative structural analysis, and that additional factors influence the intraoperative decision to abort resection, such as the adjacency of other vulnerable structures. The TTD was also significantly correlated with variations in motor evoked potential (MEP) responses (no/reversible decrease vs. irreversible decrease; p = 0.03). Conclusions: The TTD approximates the TRD well, confirming the best predictive parameter and giving strength to the nTMS-based risk stratification model. Our analysis of TRD supports the use of the nTMS-based TTD measurement to estimate the resection preoperatively, also confirming the 8 mm cutoff. Nevertheless, the TRD proved to have a slightly stronger correlation with the outcome as the surgeon’s experience, anatomofunctional knowledge, and MEP observations influence the expected EOR.

Haemospermia in the Real- Life Setting: a New High-Risk Stratification

We aimed to validate the EAU guidelines in a homogeneous cohort of men with haemospermia, and to identify a novel and better performing risk stratification compared to EAU guidelines. Data from 283 consecutive patients complaining of a single episode/recurrent haemospermia were retrospectively analysed. Patients were stratified into low vs. high-risk according to EAU guidelines, whose diagnostic performance was then validated. We identified a new risk stratification model based on clinical factors associated with i) positive semen culture and ii) prostate cancer (PCa) and bladder cancer (BC). Diagnostic accuracy of the two predictive models (EAU vs. New) was assessed and decision curve analyses (DCA) tested their clinical benefit. Overall, 259 (91.5%) were high-risk and 24 (8.5%) low risk according to the EAU guidelines. Recurrent haemospermia was reported by 134 (47.4%) patients. 126 (44.5%) had baseline CCI score ≥ 1. At MVA logistic regression analysis, history of recurrent genito – urinary tract infections was identified as a predictor for positive semen culture (OR: 3.39, 95% CI: 1.77 – 6.57, p=0.002). Likewise, baseline CCI ≥ 1 was identified as a predictor for PCa and BC (OR: 1.55, 95% CI: 1.17 – 2.04, p=0.009). Sensitivity, specificity, and AUC of the EAU guidelines were 13.3%, 89.2% and 51% respectively, whereas the new model performed substantially better: 98.9%, 58% and 78% respectively. The application of the EAU guidelines risk stratification does not ensure proper identification of high-risk patients complaining of haemospermia. We propose a novel, better performing and easily implementable risk stratification tool.

Synovial Sarcoma in Children, Adolescents, and Young Adults: A Report From the Children's Oncology Group ARST0332 Study

PURPOSE Synovial sarcoma (SS) is the second most common malignant soft tissue tumor in children. ARST0332 evaluated a risk-based treatment strategy for young patients with soft tissue sarcoma designed to limit therapy for low-risk (LR) disease and to test neoadjuvant chemoradiotherapy for unresected higher-risk disease. METHODS Newly diagnosed patients with SS age < 30 years were assigned to four treatment arms based on disease features: A (surgery only), B (55.8 Gy radiotherapy [RT]), C (ifosfamide and doxorubicin [ID] chemotherapy plus 55.8 Gy RT), and D (neoadjuvant ID and 45 Gy RT, then surgery and RT boost based on margins followed by adjuvant ID). Patients treated in Arms A and B were considered LR, arms C and D without metastases as intermediate-risk (IR), and those with metastases as high-risk (HR). RESULTS Of the 146 patients with SS enrolled, 138 were eligible and evaluable: LR (46), IR (71), and HR (21). Tumors were 80% extremity, 70% > 5 cm, 70% high-grade, 62% invasive, 95% deep, and 15% metastatic. Treatment was on arm A (29.7%), B (3.6%), C (16.7%), and D (50%). There were no toxic deaths and four unexpected grade 4 adverse events. By risk group, at a median follow-up of 6.8 years, estimated 5-year event-free survival was LR 82%, IR 70%, and HR 8%, and overall survival was LR 98%, IR 89%, and HR 13%. After accounting for the features that defined risk category, none of the other patient or disease characteristics (age, sex, tumor site, tumor invasiveness, and depth) improved the risk stratification model. CONCLUSION The risk-based treatment strategy used in ARST0332 produced favorable outcomes in patients with nonmetastatic SS relative to historical controls despite using RT less frequently and at lower doses. The outcome for metastatic SS remains unsatisfactory and new therapies are urgently needed.

Risk stratification model for telemedicine-based cardiac rehabilitation

Background Physical training (PhT) is highly cost-benefit maneuver in patients with heart disease, as a part of an integral Cardiac Rehabilitation Program. Exercise-related adverse outcomes are low, mainly due to an adequate cardiovascular risk stratification and the correct prescription and supervision of PhT. Exercise testing (ET) is the cornerstone of this process. Advances in telecommunication technologies have boosted the possibility to deliver cardiac rehabilitation via the internet, a low cost and non-face-to-face intervention. However, it is not advisable to perform a remote stress test through digital media. Purpose The aim of this study is to estimate the effect of excluding exercise test data from the traditional risk stratification model on the prediction of individual adverse outcomes. Methods A cohort of patients with heart disease who participated in an outpatient hospital-based cardiac rehabilitation program was studied. All patients underwent a clinical evaluation, along with an ET. The data obtained were used to stratify the risk of adverse events during PhT. The physical exercise program was prescribed on an individual basis. Each patient performed 30 minutes of cycle ergometry, five times a week, with a moderate effort perception (6–20 Borg scale). All sessions were supervised by a cardiologist using continuous ECG telemetry and blood pressure measurement. Resistance training was complemented with a gymnastic circuit (kinesiotherapy). A bivariate and a logistic regression multivariable analysis were performed with clinical or paraclinical variables that had been previously used in risk stratification models and showed a statistically association with the outcome (traditional model). In order to simulate the lack of an exercise stress test, these data were excluded from multivariate regression model (TELERISK), Figure 1. Results Six hundred and thirty-nine patients with cardiovascular disease were studied. No major adverse outcome was recorded. Patients presented several minor adverse outcomes, including mainly arrhythmias (n=485), such as sinus bradycardia, sinus pauses, premature supraventricular complexes, supraventricular tachycardia, atrial fibrillation, premature ventricular complexes, ventricular bigeminy, ventricular couplets and non-sustained ventricular tachycardia. Other minor outcomes were exercise-induced ischemia (n=31), exercise-induced hypotension (n=15), hypertensive response to exercise (n=31) and dizziness (n=7). The predictive capacity of the TELERISK model was significantly lower (AUC=0.661) than that observed for the traditional model (AUC=0.766), Figure 2. Conclusion The predictive capacity of the risk stratification model for adverse events during physical training in patients with cardiovascular disease decreases significantly when excluding data from the exercise test. FUNDunding Acknowledgement Type of funding sources: None. Figure 1. Telerisk multivariable model Figure 2. Outcome prediction ROC curve

An evaluation of patient workflow in hematology clinics at a university hospital referred for the workup of monoclonal gammopathy of undetermined significance (MGUS).

207 Background: Monoclonal Gammopathy of Undetermined Significance (MGUS) is an asymptomatic premalignant condition that can be a precursor to multiple myeloma and lymphoproliferative disorders. There exists no best practice for the workup of MGUS, despite the number of patients diagnosed every year. We evaluated the workup of MGUS patients at a University Hospital Hematology clinic before and after implementation of an algorithm based on the Mayo Clinic Risk Stratification Model. Methods: This was a single-center IRB-approved retrospective study. Charts of 132 patients referred for MGUS were reviewed across two groups (A: June 2019 -May 2020 and B: June-Dec 2020). Use of the Mayo Clinic Risk Stratification Model for MGUS was implemented in May 2020. Data regarding initial work up, bone marrow studies and imaging were collected. Statistical analyses were performed using R software for computing (4.0.4). Results: Patient demographics and those who did not need further work up per the algorithm are summarized in table. All 86 new (100%) referrals had an initial CBC, creatinine, calcium, SPEP, and IFE while 7(8.1%) did not have an FLC assay. 43(50%) patients had a 24-hour urine protein electrophoresis. 65.1% (56/86) [group A: 26; group B: 30] met the criteria for no extended workup; 39.3% of these (22/56) underwent imaging while 7.1% (4/56) underwent bone marrow exam. After implementation of the algorithm, the number of patients who underwent imaging studies decreased from 50% (13/26) to 30% (9/30). Skeletal survey was the most ordered imaging modality (90.1%,20/22). Conclusions: Our study highlights the overutilization of imaging studies in low-risk MGUS patients. Approximately 50% of patients with MGUS are low risk with a lifetime risk of progression being less than 2%. In these patients avoiding extensive testing will minimize costs without adversely affecting clinical outcomes. We recommend a dedicated MGUS clinic to improve workup and monitoring of these patients. [Table: see text]

Bicentric validation of the navigated transcranial magnetic stimulation motor risk stratification model

OBJECTIVE The authors sought to validate the navigated transcranial magnetic stimulation (nTMS)–based risk stratification model. The postoperative motor outcome in glioma surgery may be preoperatively predicted based on data derived by nTMS. The tumor-to-tract distance (TTD) and the interhemispheric resting motor threshold (RMT) ratio (as a surrogate parameter for cortical excitability) emerged as major factors related to a new postoperative deficit. METHODS In this bicentric study, a consecutive prospectively collected cohort underwent nTMS mapping with diffusion tensor imaging (DTI) fiber tracking of the corticospinal tract prior to surgery of motor eloquent gliomas. The authors analyzed whether the following items were associated with the patient’s outcome: patient characteristics, TTD, RMT value, and diffusivity parameters (fractional anisotropy [FA] and apparent diffusion coefficient [ADC]). The authors assessed the validity of the published risk stratification model and derived a new model. RESULTS A new postoperative motor deficit occurred in 36 of 165 patients (22%), of whom 20 patients still had a deficit after 3 months (13%; n3 months = 152). nTMS-verified infiltration of the motor cortex as well as a TTD ≤ 8 mm were confirmed as risk factors. No new postoperative motor deficit occurred in patients with TTD > 8 mm. In contrast to the previous risk stratification, the RMT ratio was not substantially correlated with the motor outcome, but high RMT values of both the tumorous and healthy hemisphere were associated with worse motor outcome. The FA value was negatively associated with worsening of motor outcome. Accuracy analysis of the final model showed a high negative predictive value (NPV), so the preoperative application may accurately predict the preservation of motor function in particular (day of discharge: sensitivity 47.2%, specificity 90.7%, positive predictive value [PPV] 58.6%, NPV 86.0%; 3 months: sensitivity 85.0%, specificity 78.8%, PPV 37.8%, NPV 97.2%). CONCLUSIONS This bicentric validation analysis further improved the model by adding the FA value of the corticospinal tract, demonstrating the relevance of nTMS/nTMS-based DTI fiber tracking for clinical decision making.