The Evolving Landscape of Biomarkers for Immune Checkpoint Blockade in Genitourinary Cancers.

In the past decade, immune checkpoint inhibitors (ICI) have been approved for treatment of genitourinary malignancies and have revolutionized the treatment landscape of these tumors. However, despite the remarkable success of these therapies in some GU malignancies, many patients' tumors do not respond to these therapies, and others may experience significant side effects, such as immune-related adverse events (iRAEs). Accordingly, biomarkers and improved prognostic tools are critically needed to help predict which patients will respond to ICI, predict and mitigate risk of developing immune-related adverse events, and inform personalized choice of therapy for each patient. Ongoing clinical and preclinical studies continue to provide an increasingly robust understanding of the mechanisms of the response to immunotherapy, which continue to inform biomarker development and validation. Herein, we provide a comprehensive review of biomarkers of the response to immunotherapy in GU tumors and their role in selection of therapy and disease monitoring.

Understanding and overcoming resistance to immunotherapy in genitourinary cancers.

The introduction of novel immunotherapies has significantly transformed the treatment landscape of genitourinary (GU) cancers, even becoming the standard of care in some settings. One such type of immunotherapy, immune checkpoint inhibitors (ICIs) like nivolumab, ipilimumab, pembrolizumab, and atezolizumab play a pivotal role by disturbing signaling pathways that limit the immune system's ability to fight tumor cells. Despite the profound impact of these treatments, not all tumors are responsive. Recent research efforts have been focused on understanding how cancer cells manage to evade the immune response and identifying the possible mechanisms behind resistance to immunotherapy. In response, ICIs are being combined with other treatments to reduce resistance and attack cancer cells through multiple cellular pathways. Additionally, novel, targeted strategies are currently being investigated to develop innovative methods of overcoming resistance and treatment failure. This article presents a comprehensive overview of the mechanisms of immunotherapy resistance in GU cancers as currently described in the literature. It explores studies that have identified genetic markers, cytokines, and proteins that may predict resistance or response to immunotherapy. Additionally, we review current efforts to overcome this resistance, which include combination ICIs and sequential therapies, novel insights into the host immune profile, and new targeted therapies. Various approaches that combine immunotherapy with chemotherapy, targeted therapy, vaccines, and radiation have been studied in an effort to more effectively overcome resistance to immunotherapy. While each of these combination therapies has shown some efficacy in clinical trials, a deeper understanding of the immune system's role underscores the potential of novel targeted therapies as a particularly promising area of current research. Currently, several targeted agents are in development, along with the identification of key immune mediators involved in immunotherapy resistance. Further research is necessary to identify predictors of response.

Immunotherapy has transformed the treatment landscape for many cancer types, including genitourinary malignancies such as renal and bladder cancers.However, not all patients or tumor types, such as prostate cancer, respond to this type of treatment.Understanding the mechanisms of immunotherapy resistance is critical for developing strategies to overcome these challenges.Primary resistance, which is present at the onset of treatment, can bedue to genetic abnormalities or immune system dysregulation. These factors alter the interactions between host cells and cancer cells.Adaptive resistance develops during therapy due to dynamic changes in the levels of growth factors, cytokines, and the tumor microenvironment (TME).Acquired resistance mainly occurs at the genetic and translational levels, involving the downregulation of critical human leukocyte antigen (HLA) molecules and interference with mutational repair.Future therapies may focus on detailed genetic profiling of patients to guide treatment selection and on the use of immune profile monitoring to assist in assessing responsiveness, alongside developing novel targeted therapies and ICIs.Further research is needed to identify predictors of response to ICIs.

Established and emerging biomarkers of immunotherapy in renal cell carcinoma.

Immunotherapies, such as immune checkpoint inhibitors, have heralded impressive progress for patient care in renal cell carcinoma (RCC). Despite this success, some patients' disease fails to respond, and other patients experience significant side effects. Thus, development of biomarkers is needed to ensure that patients can be selected to maximize benefit from immunotherapies. Improving clinicians' ability to predict which patients will respond to immunotherapy and which are most at risk of adverse events - namely through clinical biomarkers - is indispensable for patient safety and therapeutic efficacy. Accordingly, an evolving suite of therapeutic biomarkers continues to be investigated. This review discusses biomarkers for immunotherapy in RCC, highlighting current practices and emerging innovations, aiming to contribute to improved outcomes for patients with RCC.

Renal cell carcinoma (RCC) is a type of kidney cancer. Treatments that target the body's immune system, called immunotherapies, are generally effective in RCC, but not all patients' cancer will respond (shrink or disappear) after receiving this treatment. Because of this, signals, called biomarkers, are needed to signal which patients' cancer will respond and which patients may experience unwanted side effects after treatment. This article highlights biomarkers that have been or are being studied for understanding immunotherapy in RCC.

Altered mental status is an independent predictor of mortality in hospitalized COVID-19 patients.

BACKGROUND/AIMS: Limited data exists on the outcomes of COVID-19 patients presenting with altered mental status (AMS). Hence, we studied the characteristics and outcomes of hospitalized COVID-19 patients who presented with AMS at our hospital in rural southwest Georgia. METHODS: Data from electronic medical records of all hospitalized COVID-19 patients from March 2, 2020, to June 17, 2020, were analyzed. Patients were divided in 2 groups, those presenting with and without AMS. Primary outcome of interest was in-hospital mortality. Secondary outcomes were needed for mechanical ventilation, need for intensive care unit (ICU) care, need for dialysis, and length of stay. All analyses were performed using SAS 9.4 and R 3.6.0. RESULTS: Out of 710 patients, 73 (10.3%) presented with AMS. Majority of the population was African American (83.4%). Patients with AMS were older and more likely to have hypertension, chronic kidney disease (CKD), cerebrovascular disease, and dementia. Patients with AMS were less likely to present with typical COVID-19 symptoms, including dyspnea, cough, fever, and gastrointestinal symptoms. Predictors of AMS included age ≥ 70 years, CKD, cerebrovascular disease, and dementia. After multivariable adjustment, patients with AMS had higher rates of in-hospital mortality (30.1% vs 14.8%, odds ratio (OR) 2.139, p = 0.019), ICU admission (43.8% vs 40.2%, OR 2.59, p < 0.001), and need for mechanical ventilation (27.4% vs 18.5%, OR 2.06, p = 0.023). Patients presenting with AMS had increased length of stay. CONCLUSIONS: Patients with COVID-19 presenting with AMS are less likely to have typical COVID-19 symptoms, and AMS is an independent predictor of in-hospital mortality, need for ICU admission, and need for mechanical ventilation.

Is Cardiopulmonary Resuscitation Futile in Coronavirus Disease 2019 Patients Experiencing In-Hospital Cardiac Arrest?

OBJECTIVES: There is limited data regarding outcomes after in-hospital cardiac arrest among coronavirus disease 2019 patients. None of the studies have reported the outcomes of in-hospital cardiac arrest in coronavirus disease 2019 patients in the United States. We describe the characteristics and outcomes of in-hospital cardiac arrest in coronavirus disease 2019 patients in rural Southwest Georgia. DESIGN: Retrospective cohort study. SETTING: Single-center, multihospital. PATIENTS: Consecutive coronavirus disease 2019 patients who experienced in-hospital cardiac arrest with attempted resuscitation. INTERVENTIONS: Attempted resuscitation with advanced cardiac life support. MEASUREMENT AND MAIN RESULTS: Out of 1,094 patients hospitalized for coronavirus disease 2019 during the study period, 63 patients suffered from in-hospital cardiac arrest with attempted resuscitation and were included in this study. The median age was 66 years, and 49.2% were males. The majority of patients were African Americans (90.5%). The most common comorbidities were hypertension (88.9%), obesity (69.8%), diabetes (60.3%), and chronic kidney disease (33.3%). Eighteen patients (28.9%) had a Charlson Comorbidity Index of 0-2. The most common presenting symptoms were shortness of breath (63.5%), fever (52.4%), and cough (46%). The median duration of symptoms prior to admission was 14 days. During hospital course, 66.7% patients developed septic shock, and 84.1% had acute respiratory distress syndrome. Prior to in-hospital cardiac arrest, 81% were on ventilator, 60.3% were on vasopressors, and 39.7% were on dialysis. The majority of in-hospital cardiac arrest (84.1%) occurred in the ICU. Time to initiation of advanced cardiac life support protocol was less than 1 minute for all in-hospital cardiac arrest in the ICU and less than 2 minutes for the remaining patients. The most common initial rhythms were pulseless electrical activity (58.7%) and asystole (33.3%). Although return of spontaneous circulation was achieved in 29% patients, it was brief in all of them. The in-hospital mortality was 100%. CONCLUSIONS: In our study, coronavirus disease 2019 patients suffering from in-hospital cardiac arrest had 100% in-hospital mortality regardless of the baseline comorbidities, presenting illness severity, and location of arrest.

Baseline use of angiotensin-converting enzyme inhibitor/AT1 blocker and outcomes in hospitalized coronavirus disease 2019 African-American patients.

OBJECTIVES: The primary objective of this study is to determine the effect of baseline use of angiotensin-converting enzyme inhibitor (ACE-i)/AT1 blocker (ARB) on mortality in hospitalized coronavirus disease 2019 (Covid-19) African-American patients. The secondary objectives are, to determine the effect of baseline use of ACE-i/ARB on the need for mechanical ventilation, new dialysis, ICU care, and on composite of above-mentioned outcomes in the same cohort. METHODS: In this retrospective study, we analyzed data using electronic medical records from all hospitalized Covid-19 African-American patients, who either died in the hospital or survived to discharge between 2 March and 22 May 2020. Patients were divided into two groups, those on ACE-i/ARB at baseline and those not on them. We used Pearson chi-square test for categorical variables, and Student's t test for continuous variables. We performed multiple logistic regression to test the primary and secondary objectives using SAS 9.4. RESULTS: Out of 531 patients included in the analysis, 207 (39%) were on ACE-i/ARB at baseline. Patients in ACE-i/ARB group were older (64 vs. 57 years, P < 0.001), and had higher prevalence of hypertension (96.6 vs. 69.4%, P < 0.001) and diabetes mellitus (55.6 vs. 34.9%, P < 0.001). There was no difference in sex, BMI, other comorbidities, and presenting illness severity among the groups. After adjustment of multiple covariates, there was no difference in outcomes between the two groups including mortality, need for mechanical ventilation, new dialysis, ICU care, as well as composite outcomes. CONCLUSION: Baseline use of ACE-i/ARB does not worsen outcomes in hospitalized Covid-19 African-American patients.