Individual Treatment Decisions Research Articles

Detecting anaplastic lymphoma kinase (ALK) gene rearrangements with next-generation sequencing remains a reliable approach in patients with non-small-cell lung cancer.

Next-generation sequencing (NGS) is rapidly becoming routine in clinical oncology practice to identify therapeutic biomarkers, including gene rearrangements in anaplastic lymphoma kinase (ALK). Our study investigated the concordance of ALK positivity evaluated by DNA-based NGS with orthogonal ALK testing methods such as fluorescence in situ hybridization (FISH), immunohistochemistry (IHC), and RNA-based NGS (RNA-NGS). Thirty-eight patients with lung adenocarcinoma who were detected with ALK rearrangements using DNA-NGS and also had adequate tissue samples submitted for FISH, IHC, and RNA-NGS, were included in this study. Of the 38 patients, RNA samples from 3 patients failed quality control for RNA-NGS. The concordance of ALK positivity was calculated relative to DNA-NGS results. The concordance rates were 97.1% (34/35) for RNA-NGS, 94.7% (36/38) for IHC, and 97.4% (37/38) for FISH. DNA-NGS detected single ALK rearrangements in 14 (35.0%) patients and complex ALK rearrangements in 26 (65.0%). RNA-NGS detected only single transcripts of the primary ALK fusions. A novel LANCL1-ALK (L7:A20) detected using DNA-NGS was detected as EML4-ALK (E13:A20) transcripts using RNA-NGS. Interestingly, patients with single ALK rearrangements were more likely to be detected with atypical isolated red signals (p < 0.001), while patients with complex ALK rearrangements were more likely to be detected with atypical split red and green signals less than 2 signal diameters apart (p < 0.001). Our study highlights the reliability of NGS in the accurate detection of specific ALK fusion variants and concomitant mutations that are crucial for individualized treatment decisions in patients with lung cancer.

Early recovery status and outcomes after sepsis-associated acute kidney injury in critically ill patients.

Acute kidney injury (AKI) is one of the common complications in critically ill septic patients, which is associated with increased risks of death, cardiovascular events, and chronic renal dysfunction. The duration of AKI and the renal function recovery status after AKI onset can affect the patient prognosis. Nevertheless, it remains controversial whether early recovery status after AKI is closely related to the prognosis in patients with sepsis-associated AKI (SA-AKI). In addition, early prediction of renal function recovery after AKI is beneficial to individualized treatment decision-making and prevention of severe complications, thus improving the prognosis. At present, there is limited clinical information on how to identify SA-AKI patients at high risk of unrecovered renal function at an early stage. The study aims to investigate the association between early recovery status after SA-AKI, identify risk factors for unrecovered renal function, and to improve patients' quality of life. We retrospectively analyzed clinical data of septic patients who were admitted to the intensive care unit (ICU) and developed AKI within the first 48 hours after ICU admission in the Second Xiangya Hospital and the Third Xiangya Hospital of Central South University from January 2015 to March 2017. Sepsis was defined based on the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). AKI was diagnosed and staged according to the 2012 Kidney Disease: Improving Global Outcomes (KDIGO) guideline. SA-AKI patients were assigned into 3 groups including a complete recovery group, a partial recovery group, and an unrecovered group based on recovery status at Day 7 after the diagnosis of AKI. Patients' baseline characteristics were collected, including demographics, comorbidities, clinical and laboratory examination information at ICU admission, and treatment within the first 24 hours. The primary outcome of the study was the composite of death and chronic dialysis at 90 days, and secondary outcomes included length of stay in the ICU, length of stay in the hospital, and persistent renal dysfunction. Multivariate regression analysis was performed to evaluate the prognostic value of early recovery status after AKI and to determine the risk factors for unrecovered renal function after AKI. Sensitivity analysis was conducted in patients who still stayed in hospital on Day 7 after AKI diagnosis, patients without premorbid chronic kidney disease, and patients with AKI Stage 2 to 3. A total of 553 SA-AKI patients were enrolled, of whom 251 (45.4%), 73 (13.2%), and 229 (41.4%) were categorized as the complete recovery group, the partial recovery group, and the unrecovered group, respectively. Compared with the complete or partial recovery group, the unrecovered group had a higher incidence of 90-day mortality (unrecovered vs partial recovery or complete recovery: 64.2% vs 26.0% or 22.7%; P<0.001) and 90-day composite outcome (unrecovered vs partial recovery or complete recovery: 65.1% vs 27.4% or 22.7%; P<0.001). The unrecovered group also had a shorter length of stay in the hospital and a larger proportion of progression into persistent renal dysfunction than the other 2 groups. After adjustment for potential confounders, patients in the unrecovered group were at an increased risk of 90-day mortality (HR=3.50, 95% CI 2.47 to 4.96, P<0.001) and 90-day composite outcome (OR=5.55, 95% CI 3.43 to 8.98, P<0.001) when compared with patients in the complete recovery group, but patients in the partial recovery group had no significant difference (P>0.05). Male sex, congestive heart failure, pneumonia, respiratory rate >20 beats per minute, anemia, hyperbilirubinemia, need for mechanical ventilation, and AKI Stage 3 were identified as independent risk factors for unrecovered renal function after AKI. The sensitivity analysis further supported that unrecovered renal function after AKI remained an independent predictor for 90-day mortality and composite outcome in the subgroups. The early recovery status after AKI is closely associated with poor prognosis in critically ill patients with SA-AKI. Unrecovered renal function within the first 7 days after AKI diagnosis is an independent predictor for 90-day mortality and composite outcome. Male sex, congestive heart failure, pneumonia, tachypnea, anemia, hyperbilirubinemia, respiratory failure, and severe AKI are risk factors for unrecovered renal function after AKI. Therefore, timely assessment for the renal function in the early phase after AKI diagnosis is essential for SA-AKI patients. Furthermore, patients with unrecovered renal function after AKI need additional management in the hospital, including rigorous monitoring, avoidance of nephrotoxin, and continuous assessment for the renal function, and after discharge, including more frequent follow-up, regular outpatient consultation, and prevention of long-term adverse events.

Immunocompromised patients have been neglected in COVID-19 trials: a call for action

Immunocompromised patients have been neglected in COVID-19 trials: a call for action

A permutation procedure to detect heterogeneous treatment effects in randomized clinical trials while controlling the type I error rate.

Secondary analyses of randomized clinical trials often seek to identify subgroups with differential treatment effects. These discoveries can help guide individual treatment decisions based on patient characteristics and identify populations for which additional treatments are needed. Traditional analyses require researchers to pre-specify potential subgroups to reduce the risk of reporting spurious results. There is a need for methods that can detect such subgroups without a priori specification while allowing researchers to control the probability of falsely detecting heterogeneous subgroups when treatment effects are uniform across the study population. We propose a permutation procedure for tuning parameter selection that allows for type I error control when testing for heterogeneous treatment effects framed within the Virtual Twins procedure for subgroup identification. We verify that the type I error rate can be controlled at the nominal rate and investigate the power for detecting heterogeneous effects when present through extensive simulation studies. We apply our method to a secondary analysis of data from a randomized trial of very low nicotine content cigarettes. In the absence of type I error control, the observed type I error rate for Virtual Twins was between 99% and 100%. In contrast, models tuned via the proposed permutation were able to control the type I error rate and detect heterogeneous effects when present. An application of our approach to a recently completed trial of very low nicotine content cigarettes identified several variables with potentially heterogeneous treatment effects. The proposed permutation procedure allows researchers to engage in secondary analyses of clinical trials for treatment effect heterogeneity while maintaining the type I error rate without pre-specifying subgroups.

Homogeneous and heterogeneous risk and prognostic factors for lung metastasis in colorectal cancer patients

BackgroundThe lung is one of the most frequent distant metastasis sites in colorectal cancer (CRC) patients; however, lung metastasis risk and prognostic factors have not been comprehensively elucidated. This study aimed to identify the homogeneous and heterogeneous lung metastasis risk and prognostic factors in CRC patients using the Surveillance, Epidemiology, and End Results (SEER) database.MethodsCRC patients registered in the SEER database between 2010 and 2016 were included to analyse risk factors for developing lung metastasis by using univariable and multivariable logistic regression. Patients diagnosed between 2010 and 2015 were selected to investigate prognostic factors for lung metastasis by conducting Cox regression. Kaplan–Meier analysis was used to estimate overall survival outcomes.ResultsA total of 10,598 (5.2%) patients with synchronous lung metastasis were diagnosed among 203,138 patients with CRC. The median survival time of patients with lung metastasis was 10.0 months (95% CI 9.6–10.5 months). Older age, unmarried status, uninsured status, poor histological differentiation, more lymphatic metastasis, CEA positivity, liver metastasis, bone metastasis and brain metastasis were lung metastasis risk and prognostic factors. Black patients and those with left colon, rectum, and stage T4 disease were more likely to develop lung metastasis, while patients with right colon cancer and no surgical treatment of the primary tumour had poor survival outcomes.ConclusionThe incidence of lung metastasis in CRC patients was 5.2%. CRC patients with lung metastasis exhibited homogeneous and heterogeneous risk and prognostic factors. These results are helpful for clinical evaluation and individual treatment decision making.

Bioinformatics analysis reveals immune prognostic markers for overall survival of colorectal cancer patients: a novel machine learning survival predictive system

ObjectivesImmune microenvironment was closely related to the occurrence and progression of colorectal cancer (CRC). The objective of the current research was to develop and verify a Machine learning survival predictive system for CRC based on immune gene expression data and machine learning algorithms.MethodsThe current study performed differentially expressed analyses between normal tissues and tumor tissues. Univariate Cox regression was used to screen prognostic markers for CRC. Prognostic immune genes and transcription factors were used to construct an immune-related regulatory network. Three machine learning algorithms were used to create an Machine learning survival predictive system for CRC. Concordance indexes, calibration curves, and Brier scores were used to evaluate the performance of prognostic model.ResultsTwenty immune genes (BCL2L12, FKBP10, XKRX, WFS1, TESC, CCR7, SPACA3, LY6G6C, L1CAM, OSM, EXTL1, LY6D, FCRL5, MYEOV, FOXD1, REG3G, HAPLN1, MAOB, TNFSF11, and AMIGO3) were recognized as independent risk factors for CRC. A prognostic nomogram was developed based on the previous immune genes. Concordance indexes were 0.852, 0.778, and 0.818 for 1-, 3- and 5-year survival. This prognostic model could discriminate high risk patients with poor prognosis from low risk patients with favorable prognosis.ConclusionsThe current study identified twenty prognostic immune genes for CRC patients and constructed an immune-related regulatory network. Based on three machine learning algorithms, the current research provided three individual mortality predictive curves. The Machine learning survival predictive system was available at: https://zhangzhiqiao8.shinyapps.io/Artificial_Intelligence_Survival_Prediction_for_CRC_B1005_1/, which was valuable for individualized treatment decision before surgery.

Construction of a Novel Immune-Related mRNA Signature to Predict the Prognosis and Immune Characteristics of Human Colorectal Cancer.

Background: Anti-cancer immunotherapeutic approaches have gained significant efficacy in multiple cancer types. However, not all patients with colorectal cancer (CRC) could benefit from immunotherapy due to tumor heterogeneity. The purpose of this study was to construct an immune-related signature for predicting the immune characteristics and prognosis of CRC. Methods: RNA-sequencing data and corresponding clinical information of patients with CRC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), and immune-related genes (IRGs) were downloaded from the Immunology Database and Analysis Portal (ImmPort). Then, we utilized univariate, lasso regression, and multivariate cox regression to identify prognostic IRGs and develop the immune-related signature. Subsequently, a nomogram was established based on the signature and other prognostic factors, and its predictive capacity was assessed by receiver operating characteristic (ROC) and decision curve analysis (DCA). Finally, associations between the signature and the immune characteristics of CRC were assessed. Results: In total, 472 samples downloaded from TCGA were divided into the training cohort (236 samples) and internal validation cohort (236 samples), and the GEO cohort was downloaded as an external validation cohort (122 samples). A total of 476 differently expressed IRGs were identified, 17 of which were significantly correlated to the prognosis of CRC patients. Finally, 10 IRGs were filtered out to construct the risk score signature, and patients were divided into low- and high-risk groups according to the median of risk scores in the training cohort. The high-risk score was significantly correlated with unfavorable survival outcomes and aggressive clinicopathological characteristics in CRC patients, and the results were further confirmed in the internal validation cohort, entire TCGA cohort, and external validation cohort. Immune infiltration analysis revealed that patients in the low-risk group infiltrated with high tumor-infiltrating immune cell (TIIC) abundances compared to the high-risk group. Moreover, we also found that the immune checkpoint biomarkers were significantly overexpressed in the low-risk group. Conclusion: The prognostic signature established by IRGs showed a promising clinical value for predicting the prognosis and immune characteristics of human CRC, which contribute to individualized treatment decisions.

A novel nine-microRNA-based model to improve prognosis prediction of renal cell carcinoma

BackgroundWith the improved knowledge of disease biology and the introduction of immune checkpoints, there has been significant progress in treating renal cell carcinoma (RCC) patients. Individual treatment will differ according to risk stratification. As the clinical course varies in RCC, it has developed different predictive models for assessing patient’s individual risk. However, among other prognostic scores, no transparent preference model was given. MicroRNA as a putative marker shown to have prognostic relevance in RCC, molecular analysis may provide an innovative benefit in the prophetic prediction and individual risk assessment. Therefore, this study aimed to establish a prognostic-related microRNA risk score model of RCC and further explore the relationship between the model and the immune microenvironment, immune infiltration, and immune checkpoints. This practical model has the potential to guide individualized surveillance protocols, patient counseling, and individualized treatment decision for RCC patients and facilitate to find more immunotherapy targets.MethodsDownloaded data of RCC from the TCGA database for difference analysis and divided it into a training set and validation set. Then the prognostic genes were screened out by Cox and Lasso regression analysis. Multivariate Cox regression analysis was used to establish a predictive model that divided patients into high-risk and low-risk groups. The ENCORI online website and the results of the RCC difference analysis were used to search for hub genes of miRNA. Estimate package and TIMER database were used to evaluate the relationship between risk score and tumor immune microenvironment (TME) and immune infiltration. Based on Kaplan-Meier survival analysis, search for immune checkpoints related to the prognosis of RCC.ResultsThere were nine miRNAs in the established model, with a concordance index of 0.702 and an area under the ROC curve of 0.701. Nine miRNAs were strongly correlated with the prognosis (P < 0.01), and those with high expression levels had a poor prognosis. We found a common target gene PDGFRA of hsa-miR-6718, hsa-miR-1269b and hsa-miR-374c, and five genes related to ICGs (KIR2DL3, TNFRSF4, LAG3, CD70 and TNFRSF9). The immune/stromal score, immune infiltration, and immune checkpoint genes of RCC were closely related to its prognosis and were positively associated with a risk score.ConclusionsThe established nine-miRNAs prognostic model has the potential to facilitate prognostic prediction. Moreover, this model was closely related to the immune microenvironment, immune infiltration, and immune checkpoint genes of RCC.

Predicting microvascular invasion in hepatocellular carcinoma: A dual-institution study on gadoxetate disodium-enhanced MRI.

Background & AimsMicrovascular invasion (MVI) is an important risk factor in hepatocellular carcinoma (HCC), but its diagnosis mandates postoperative histopathologic analysis. We aimed to develop and externally validate a predictive scoring system for MVI.MethodsFrom July 2015 to November 2020, consecutive patients underwent surgery for HCC with preoperative gadoxetate disodium (EOB)‐enhanced MRI was retrospectively enrolled. All MR images were reviewed independently by two radiologists who were blinded to the outcomes. In the training centre, a radio‐clinical MVI score was developed via logistic regression analysis against pathology. In the testing centre, areas under the receiver operating curve (AUCs) of the MVI score and other previous MVI schemes were compared. Overall survival (OS) and recurrence‐free survival (RFS) were analysed by the Kaplan–Meier method with the log‐rank test.ResultsA total of 417 patients were included, 195 (47%) with pathologically‐confirmed MVI. The MVI score included: non‐smooth tumour margin (odds ratio [OR] = 4.4), marked diffusion restriction (OR = 3.0), internal artery (OR = 3.0), hepatobiliary phase peritumoral hypointensity (OR = 2.5), tumour multifocality (OR = 1.6), and serum alpha‐fetoprotein >400 ng/mL (OR = 2.5). AUCs for the MVI score were 0.879 (training) and 0.800 (testing), significantly higher than those for other MVI schemes (testing AUCs: 0.648–0.684). Patients with model‐predicted MVI had significantly shorter OS (median 61.0 months vs not reached, P < .001) and RFS (median 13.0 months vs. 42.0 months, P < .001) than those without.ConclusionsA preoperative MVI score integrating five EOB‐MRI features and serum alpha‐fetoprotein level could accurately predict MVI and postoperative survival in HCC. Therefore, this score may aid in individualized treatment decision making.

Platelet FcγRIIa Expression in Ischemic Stroke: A Marker of Increased Platelet Reactivity

Background Platelet FcγRIIa amplifies platelet activation and, thus, increased expression identifies patients with increased platelet reactivity. Previous work has demonstrated that platelet FcγRIIa can identify patients at high and low risk of subsequent cardiovascular events after myocardial infarction (MI). This study was designed to compare platelet expression of FcγRIIa in patients with stroke and transient ischemic attack (TIA) with that in patients with a recent MI. Methods Patients were enrolled based on an admitting diagnosis of stroke/TIA, and the discharge diagnosis was used to categorize patients into stroke/TIA (n=99) and other causes of neurologic dysfunction (hemorrhagic, trauma, toxic, and seizure; n=14). Patients with stroke/TIA were divided into embolic (both cardioembolic and thromboembolic; n=32) and not embolic causes (n=67). Results were compared with platelet FcγRIIa expression in patients with recent MI from a previous study (n=197). Platelet expression of FcγRIIa (molecules of FcγRIIa/platelet) was quantified with the use of flow cytometry. Results are mean±SD. Results Platelet expression of FcγRIIa was similar in patients with ischemic (both embolic and nonembolic) stroke/TIA (11 332±4127), embolic (11 204±3889) and nonembolic (11 393±4263) causes, and MI (11 479±2405). Patients with other causes of neurologic dysfunction had modestly but not significantly lower platelet expression of FcγRIIa (9389±2883; P =0.13). Conclusions Platelet expression of FcγRIIa was similar in patients with stroke/TIA and recent MI. These results support future studies designed to determine whether platelet FcγRIIa expression can discriminate risk of subsequent stroke/TIA and its potential use as a precision tool capable of guiding individualized treatment decisions.

Circulating Levels of the Cardiovascular Biomarkers ST2 and Adrenomedullin Predict Outcome within a Randomized Phase III Lung Cancer Trial (RASTEN).

Simple SummaryCardiovascular disease is common in patients with small cell lung cancer, partly reflecting its high correlation with smoking. Cardiovascular comorbidities may limit patient tolerance to cytotoxic drugs, thereby influencing the choice and intensity of treatment and, ultimately, patient survival. In light of the challenges relating to assessing cardiovascular status clinically in newly diagnosed lung cancer, objective biomarkers of cardiovascular vulnerability are warranted. Here, we show that circulating levels of ST2, an established biomarker in heart failure, and adrenomedullin, a vasodilator peptide known to reflect several aspects of cardiovascular status, strongly correlate with survival in small cell lung cancer. Our data, which are based on a large, randomized trial cohort, suggest the potential use of cardiovascular biomarkers in guiding clinicians in making individualized treatment decisions.Cardiovascular comorbidity is common in small cell lung cancer (SCLC) and may significantly affect treatment tolerability and patient outcome. Still, there are no established biomarkers for objective and dynamic assessment as a tool for improved treatment decisions. We have investigated circulating levels of midregional-pro-adrenomedullin (MR-proADM), midregional-pro-atrial-natriuretic peptide (MR-proANP), copeptin (surrogate for vasopressin) and suppression-of-tumorigenicity-2 (ST2), all known to correlate with various aspects of cardiovascular function, in a SCLC cohort (N = 252) from a randomized, controlled trial (RASTEN). For all measured biomarkers, protein levels were inversely associated with survival, particularly with ST2 and MR-proADM, where the top versus bottom quartile was associated with an adjusted hazard ratio of 2.40 (95% CI 1.44–3.98; p = 0.001) and 2.18 (95% CI 1.35–3.51; p = 0.001), respectively, in the entire cohort, and 3.43 (95% CI 1.73–6.79; p < 0.001) and 3.49 (95% CI 1.84–6.60; p < 0.001), respectively, in extensive disease patients. A high combined score of MR-proADM and ST2 was associated with a significantly reduced median OS of 7.0 months vs. 14.9 months for patients with a low combined score. We conclude that the cardiovascular biomarkers MR-proADM and ST2 strongly correlate with survival in SCLC, warranting prospective studies on the clinical utility of MR-proADM and ST2 for improved, individualized treatment decisions.

The Prognostic Value of Integrated Analysis of Inflammation and Hypoxia-Related Genes in Idiopathic Pulmonary Fibrosis.

Currently, the aetiology and pathogenesis of idiopathic pulmonary fibrosis (IPF) are still largely unclear. Moreover, patients with IPF exhibit a considerable difference in clinical presentation, treatment, and prognosis. Optimal biomarkers or models for IPF prognosis are lacking. Therefore, this study quantified the levels of various hallmarks using a single-sample gene set enrichment analysis algorithm. The hazard ration was calculated using Univariate Cox regression analysis based on the transcriptomic profile of bronchoalveolar lavage cells and clinical survival information. Afterwards, weighted Gene Co-expression Network Analysis was performed to construct a network between gene expression, inflammation response, and hypoxia. Subsequently, univariate Cox, random forest, and multivariate Cox regressions were applied to develop a robust inflammation and hypoxia-related gene signature for predicting clinical outcomes in patients with IPF. Furthermore, a nomogram was constructed to calculate risk assessment. The inflammation response and hypoxia were identified as latent risk factors for patients with IPF. Five genes, including HS3ST1, WFDC2, SPP1, TFPI, and CDC42EP2, were identified that formed the inflammation-hypoxia-related gene signature. Kaplan-Meier plotter showed that the patients with high-risk scores had a worse prognosis than those with low-risk scores in training and validation cohorts. The time-dependent concordance index and the receiver operating characteristic analysis revealed that the risk model could accurately predict the clinical outcome of patients with IPF. Therefore, this study contributes to elucidating the role of inflammation and hypoxia in IPF, which can aid in assessing individual prognosis and personalised treatment decisions.

The impact of bowel dysfunction on health-related quality of life after rectal cancer surgery: a systematic review.

Symptoms of bowel dysfunction after sphincter-preserving rectal cancer surgery have an important impact on health-related quality of life (HRQOL), but that relationship is complex. A better understanding of this relationship allows for better informed shared decision-making about surgery. Our objective was to perform a systematic review to determine which HRQOL domains are most affected by postoperative bowel dysfunction. A systematic review of the CINAHL, Cochrane Library, Embase, Medline, PsycInfo, PubMed, Web of Science, and Scopus databases was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We included studies that evaluated bowel function after sphincter-preserving rectal cancer surgery and assessed HRQOL using a validated instrument. The quality of HRQOL analysis was assessed using an 11-item checklist. The main outcome was the impact bowel dysfunction had on global and domain specific quality-of-life indices. The impact was evaluated for clinical relevance using the Minimum Clinical Important Difference (MCID) for each specific HRQOL instrument. Out of 952 unique citations, 103 studies were full-text reviews. Eighteen studies met the inclusion criteria (4 prospective cohorts and 9 cross-sectional studies). Of the 15 studies with long-term follow-up, the time to assessment after surgery ranged from 1.2 to 14.6years. The low anterior resection syndrome score and European Organization for Research and Treatment core quality-of-life questionnaire (EORTC QLQ-C30) were the most commonly used instruments. Medium and large magnitudes in MCID were seen for global health, social functioning, emotional functioning, fatigue, diarrhea, and financial difficulties. Among included studies, the most consistently reported functional domains affected by bowel function were social functioning and emotional functioning. Following sphincter-preserving rectal cancer surgery, poor bowel function mainly affects the social and emotional functional domains of HRQOL, which in turn impact global scores. This finding can help inform patients about expected changes in HRQOL after rectal cancer surgery and facilitate individualized treatment decisions.

Molecular Imaging and Theragnostics of Thyroid Cancers.

Simple SummaryAccording to the American Cancer Society, approximately 53,000 new cases of thyroid cancer were diagnosed and more than 2200 people died from the disease in 2020. New developments in molecular imaging are significantly improving thyroid cancer diagnostics and therapy. Continuous research in molecular imaging techniques additionally contributes to an understanding of a variety of diseases and enables more efficient care of thyroid cancer patients. Molecular imaging-based personalized therapy has been a fascinating concept for individualized therapeutic strategy, which is able to attain the highest efficacy and reduce adverse effects in certain patients. Theragnostics, which integrates diagnostic testing to detect molecular targets for particular therapeutic modalities, is one of the key technologies that contributes to the success of personalized medicine. This review details the inception of molecular imaging and theragnostic applications for thyroid cancer management.Molecular imaging plays an important role in the evaluation and management of different thyroid cancer histotypes. The existing risk stratification models can be refined, by incorporation of tumor-specific molecular markers that have theranostic power, to optimize patient-specific (individualized) treatment decisions. Molecular imaging with varying radioisotopes of iodine (i.e., 131I, 123I, 124I) is an indispensable component of dynamic and theragnostic risk stratification of differentiated carcinoma (DTC) while [18F]F-fluorodeoxyglucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) helps in addressing disease aggressiveness, detects distant metastases, and risk-stratifies patients with radioiodine-refractory DTC, poorly differentiated and anaplastic thyroid cancers. For medullary thyroid cancer (MTC), a neuroendocrine tumor derived from thyroid C-cells, [18F]F-dihydroxyphenylalanine (6-[18F]FDOPA) PET/CT and/or [18F]FDG PET/CT can be used dependent on serum markers levels and kinetics. In addition to radioiodine therapy for DTC, some theragnostic approaches are promising for metastatic MTC as well. Moreover, new redifferentiation strategies are now available to restore uptake in radioiodine-refractory DTC while new theragnostic approaches showed promising preliminary results for advanced and aggressive forms of follicular-cell derived thyroid cancers (i.e., peptide receptor radiotherapy). In order to help clinicians put the role of molecular imaging into perspective, the appropriate role and emerging opportunities for molecular imaging and theragnostics in thyroid cancer are discussed in our present review.

Myelofibrosis: Genetic Characteristics and the Emerging Therapeutic Landscape.

Primary myelofibrosis (PMF) is one of three myeloproliferative neoplasms (MPN) that are morphologically and molecularly inter-related, the other two being polycythemia vera (PV) and essential thrombocythemia (ET). MPNs are characterized by JAK-STAT-activating JAK2, CALR, or MPL mutations that give rise to stem cell-derived clonal myeloproliferation, which is prone to leukemic and, in case of PV and ET, fibrotic transformation. Abnormal megakaryocyte proliferation is accompanied by bone marrow fibrosis and characterizes PMF, while the clinical phenotype is pathogenetically linked to ineffective hematopoiesis and aberrant cytokine expression. Among MPN-associated driver mutations, type 1-like CALR mutation has been associated with favorable prognosis in PMF, while ASXL1, SRSF2, U2AF1-Q157, EZH2, CBL, and K/NRAS mutations have been shown to be prognostically detrimental. Such information has enabled development of exclusively genetic (GIPSS) and clinically integrated (MIPSSv2) prognostic models that facilitate individualized treatment decisions. Allogeneic stem cell transplantation remains the only treatment modality in MF with the potential to prolong survival, whereas drug therapy, including JAK2 inhibitors, is directed mostly at the inflammatory component of the disease and is therefore palliative in nature. Similarly, disease-modifying activity remains elusive for currently available investigational drugs, while their additional value in symptom management awaits controlled confirmation. There is a need for genetic characterization of clinical observations followed by in vitro and in vivo preclinical studies that will hopefully identify therapies that target the malignant clone in MF to improve patient outcomes.

Prospective evaluation of a comprehensive geriatric assessment (CGA) in multidisciplinary bladder cancer care: Feasibility and impact on decisional conflict.

479 Background: Commonly utilized risk stratification tools demonstrate inconsistent associations with salient clinical outcomes in bladder cancer leading to a disproportionate reliance on providers’ subjective impression of a patient’s fitness for therapy. Current guidelines advocate for use of a CGA to quantify vulnerabilities in older ( &gt; 65 years) patients before treatment selection. Our objective was to prospectively evaluate CGA in our Bladder Cancer Multidisciplinary Clinic (BCMC). We hypothesized that CGA implementation would be feasible and that discussion of the results during shared decision-making would be associated with reduced patient-reported decisional conflict. Methods: Patients seen in BCMC were prospectively enrolled from 6/1/20 to 7/20/21. In the first 3 months, participants underwent non-standardized risk stratification (“Routine cohort”, N = 27). Between 9/1/20 and 7/20/21, participants completed a CGA incorporating validated assessments of frailty, functional status, multimorbidity, nutrition, cognition, and mental health (“CGA cohort”, N = 67). Results were shared with patients during BCMC visits. All patients and providers (three physicians per clinic from: Uro-Oncology, Medical Oncology, and Radiation Oncology) completed a follow-up survey including the Decisional Conflict Scale (DCS). Time required to complete the CGA, completion rates, and patient-reported burden were assessed. Concordance of patient- and provider-reported decisional conflict was compared between Routine and CGA cohorts. Results: Of 138 eligible patients, 94 patients were successfully enrolled (68%) with median age of 72 years, ECOG PS ≥3 in 13%, and Charlson Comorbidity Index ≥3 in 18%, of whom 18% were women. Most patients had pT2 bladder cancer (87%; cN+ and M1 in 23.4% and 9.6%, respectively). CGA component completion rates were 79-100%. Survey response rates were high (patients: 77%, providers: 86%), and most (86%) patients felt that the CGA was, at most, minimally burdensome. Vulnerabilities detected across CGA domains triggered relevant referrals. Patient-reported median (IQR) DCS scores were numerically higher (e.g. greater decisional conflict) for the CGA cohort: (27 [14-33] vs 16 [2-30] for Routine patients, p = 0.28). Provider- and provider reported DCS score was correlated in the CGA (p = 0.04), but not the Routine cohort (p = 0.07). Conclusions: We prospectively evaluated use of CGAs in bladder cancer care and found that CGAs were successfully implemented with high rates of completion and low rates of perceived burden. Notably, in this pilot cohort of 94 patients, DCS scores did not differ significantly between patients and providers with CGA use. Future work will evaluate associations between individual instruments, treatment decisions, clinical outcomes and patient-reported quality of life measures.

Towards Personalized Medicine in Myasthenia Gravis: Role of Circulating microRNAs miR-30e-5p, miR-150-5p and miR-21-5p

Myasthenia gravis (MG) is an autoimmune neuromuscular disease characterized by fatigable skeletal muscle weakness with a fluctuating unpredictable course. One main concern in MG is the lack of objective biomarkers to guide individualized treatment decisions. Specific circulating serum microRNAs (miRNAs) miR-30e-5p, miR-150-5p and miR-21-5p levels have been shown to correlate with clinical course in specific MG patient subgroups. The aim of our study was to better characterize these miRNAs, regardless of the MG subgroup, at an early stage from diagnosis and determine their sensitivity and specificity for MG diagnosis, as well as their predictive power for disease relapse. Serum levels of these miRNAs in 27 newly diagnosed MG patients were compared with 245 healthy individuals and 20 patients with non-MG neuroimmune diseases. Levels of miR-30e-5p and miR-150-5p significantly differed between MG patients and healthy controls; however, no difference was seen compared with patients affected by other neuroimmune diseases. High levels of miR-30e-5p predicted MG relapse (p = 0.049) with a hazard ratio of 2.81. In summary, miR-150-5p is highly sensitive but has low specificity for MG, while miR-30e-5p has the greatest potential as a predictive biomarker for the disease course in MG, regardless of subgroup.

Procollagen-Lysine, 2-Oxoglutarate 5-Dioxygenase Family: Novel Prognostic Biomarkers and Tumor Microenvironment Regulators for Lower-Grade Glioma.

Lower-grade glioma (LGG) is a group of tumors arising from the cells of the central nervous system. Although various therapy interventions are used, the prognosis remains different. Novel biomarkers are needed for the prognosis of disease and novel therapeutic strategies in LGG. The procollagen-lysine, 2-oxoglutarate 5-dioxygenase (PLOD) family contains three members and is related to multiple cancers, yet it was not investigated in LGG. Data from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) cohorts were used to analyze the role of PLOD in LGG. As the PLOD family is involved in processes, such as tumor formation and cancer metastasis, we focused on its relationship to the tumor microenvironment (TME) in LGG. A high expression of the PLOD family relates to poor prognosis and high infiltration of immune cells within the TME. The expression level of the PLOD family might become a novel biomarker for prognosis and is a potential target for individual treatment decisions in LGG.

Quantitative Analysis of Plasma Cell-Free DNA and Its DNA Integrity and Hypomethylation Status as Biomarkers for Tumor Burden and Disease Progression in Patients with Metastatic Neuroendocrine Neoplasias.

Simple SummaryNeuroendocrine neoplasias (NEN) are a heterogeneous group of frequent slow-progressing malignant tumors for which a reliable marker for tumor relapse and progression is still lacking. Previously, circulating cell-free DNA and its global methylation status and fragmentation rate have been proposed to be valuable prognostic tumor markers in a variety of malignancies. In the current study, we compared plasma cell-free DNA (cfDNA) properties of NEN patients with a healthy control group and a group of surgically cured patients. Our results revealed significantly higher plasma cfDNA concentrations with increased fragmentation and hypomethylation in patients with advanced metastatic NEN, which was strongly associated with tumor load and could help to differentiate between metastasized disease and presumably cured patients. This suggests that the combined analysis of plasma cfDNA characteristics is a potent and sensitive prognostic and therapeutic biomarker for tumor burden and disease progression in patients with neuroendocrine neoplasias.Background: Neuroendocrine neoplasia (NEN) encompasses a diverse group of malignancies marked by histological heterogeneity and highly variable clinical outcomes. Apart from Chromogranin A, specific biomarkers predicting residual tumor disease, tumor burden, and disease progression in NEN are scant. Thus, there is a strong clinical need for new and minimally invasive biomarkers that allow for an evaluation of the prognosis, clinical course, and response to treatment of NEN patients, thereby helping implement individualized treatment decisions in this heterogeneous group of patients. In the current prospective study, we evaluated the role of plasma cell-free DNA concentration and its global hypomethylation and fragmentation as possible diagnostic and prognostic biomarkers in patients with neuroendocrine neoplasias. Methods: The plasma cfDNA concentration, cfDNA Alu hypomethylation, and LINE-1 cfDNA integrity were evaluated prospectively in 63 NEN patients with presumably cured or advanced metastatic disease. The cfDNA characteristics in NEN patients were compared to the results of a group of 29 healthy controls and correlated with clinical and histopathological data of the patients. Results: Patients with advanced NEN showed a significantly higher cfDNA concentration and percentage of Alu hypomethylation and a reduced LINE-1 cfDNA integrity as compared to the surgically cured NET patients and the healthy control group. The increased hypomethylation and concentration of cfDNA and the reduced cfDNA integrity in NEN patients were strongly associated with tumor burden and poor prognosis, while no correlation with tumor grading, differentiation, localization, or hormonal activity could be found. Multiparametric ROC analysis of plasma cfDNA characteristics was able to distinguish NEN patients with metastatic disease from the control group and the cured NEN patients with AUC values of 0.694 and 0.908, respectively. This was significant even for the group with only a low tumor burden. Conclusions: The present study, for the first time, demonstrates that the combination of plasma cfDNA concentration, global hypomethylation, and fragment length pattern has the potential to serve as a potent and sensitive prognostic and therapeutic “liquid biopsy” biomarker for tumor burden and disease progression in patients with neuroendocrine neoplasias.

Abstract P2-01-16: Targeted sequencing of plasma-derived vs. urinary cfDNA from patients with triple negative breast cancer

Abstract Background: In breast cancer, genetic profiling of circulating cell-free DNA (cfDNA) from blood plasma was shown to have good potential for clinical use and might help to find individual treatment options and to monitor metastatic relapse as well as intratumoral heterogeneity. Due to limited therapy options and high risk of acquired treatment resistance based on genetic alterations of the tumor, particularly, women diagnosed with the aggressive triple negative breast cancer (TNBC) subtype might benefit from serial mutation profiling during disease courses. Here, cfDNA derived from patients’ urine might offer promising opportunities for non-invasive monitoring at frequent intervals. In this pilot study, we investigated plasma-derived and matching urinary cfDNA samples obtained from 15 presurgical TNBC patients using a targeted sequencing approach to identify common breast cancer-related genetic alterations in both bodyfluids. Methods: Blood plasma and urine samples were processed within 4 hrs after collection. We successfully adapted the manufacturer’s instructions to yield increased concentrations of extracted plasma-derived and urinary cfDNA (QIAamp MinElute ccfDNA Kit, QIAGEN). After quality control of cfDNA fragments, matched samples were applied to library preparation and target enrichment with a commercially available diagnostic breast cancer specific 93-gene panel service (QIAGEN). Libraries were analyzed by paired-end sequencing on a NextSeq550 (Illumina Inc.) instrument followed by bioinformatical analysis with QIAGEN Biomedical Genomics Workbench and subsequent interpretation of variants using QCI Interpret Translational Software (QIAGEN). Results: In the cohort, 3339 somatic breast-cancer related genetic alterations (VAF ≥ 3%) were detected, whereof 1222 vs. 2117 variants were found in plasma-derived vs. urinary cfDNA, respectively. Further, 431 variants were found in cfDNA derived from both body fluids. Per sample, we found a median number of 66 variants in plasma vs. 110 variants in urinary cfDNA. Interestingly, a median number of 31 shared variants was found per matched plasma-derived and urinary cfDNA sample resulting in a 46% recovery rate of plasma-derived mutations in urinary cfDNA (and vice versa only a 16% recovery rate of urinary cfDNA variants in plasma) throughout the cohort. Interestingly, QCI analysis revealed that 48 of the mutations found in both body fluids were pathogenic, resulting in a median number of 4 pathogenic variants per sample. The recovery rate of pathogenic plasma-derived variants in urinary cfDNA was 63% and vice versa, 66% of pathogenic urinary variants could be detected in the matched plasma samples. Further, 33 of the shared mutations were likely pathogenic. Among the patients, the most frequently occurring pathogenic and likely pathogenic mutated genes were NF1, CHEK2, KMT2C and PTEN in both body fluids. Noteworthy, a pathogenic CHEK2 (T519M) variant was found in all 30 samples and two pathogenic NF1 variants (T467I + c.2325+3A&amp;gt;G) as well as a pathogenic PTEN variant (C136Y) were also very frequent in the cohort. Conclusion: Taken together, our results indicated that both plasma-derived and urinary cfDNA from TNBC patients could be analyzed in a sufficient manner using a targeted sequencing approach. Both body fluids appear to be valuable sources bearing complementary information regarding the genetic tumor profile, which might be relevant for disease monitoring and individual treatment decisions. Further analyses of a larger patient cohort using adequate bioinformatics algorithms are required to find associations between somatic variants in both cfDNA sources. Key words: cfDNA, breast cancer, targeted sequencing, somatic variants, mutation, urine, plasma Citation Format: Henrike Herzog, Bahriye Aktas, Ivonne Nel. Targeted sequencing of plasma-derived vs. urinary cfDNA from patients with triple negative breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-01-16.