Single-cell transcriptomic-informed deconvolution of bulk data identifies immune checkpoint blockade resistance in urothelial cancer.

Interactions within the tumor microenvironment (TME) significantly influence tumor progression and treatment responses. While single-cell RNA sequencing (scRNA-seq) and spatial genomics facilitate TME exploration, many clinical cohorts are assessed at the bulk tissue level. Integrating scRNA-seq and bulk tissue RNA-seq data through computational deconvolution is essential for obtaining clinically relevant insights. Our method, ProM, enables the examination of major and minor cell types. Through evaluation against existing methods using paired single-cell and bulk RNA sequencing of human urothelial cancer (UC) samples, ProM demonstrates superiority. Application to UC cohorts treated with immune checkpoint inhibitors reveals pre-treatment cellular features associated with poor outcomes, such as elevated SPP1 expression in macrophage/monocytes (MM). Our deconvolution method and paired single-cell and bulk tissue RNA-seq dataset contribute novel insights into TME heterogeneity and resistance to immune checkpoint blockade.

Cooperativity of c-MYC with Krüppel-Like Factor 6 Splice Variant 1 induces phenotypic plasticity and promotes prostate cancer progression and metastasis.

Metastasis remains a major cause of morbidity and mortality in men with prostate cancer, and the functional impact of the genetic alterations, alone or in combination, driving metastatic disease remains incompletely understood. The proto-oncogene c-MYC, commonly deregulated in prostate cancer. Transgenic expression of c-MYC is sufficient to drive the progression to prostatic intraepithelial neoplasia and ultimately to moderately differentiated localized primary tumors, however, c-MYC-driven tumors are unable to progress through the metastatic cascade, suggesting that a "second-hit" is necessary in the milieu of aberrant c-MYC-driven signaling. Here, we identified cooperativity between c-MYC and KLF6-SV1, an oncogenic splice variant of the KLF6 gene. Transgenic mice that co-expressed KLF6-SV1 and c-MYC developed progressive and metastatic prostate cancer with a histological and molecular phenotype like human prostate cancer. Silencing c-MYC expression significantly reduced tumor burden in these mice supporting the necessity for c-MYC in tumor maintenance. Unbiased global proteomic analysis of tumors from these mice revealed significantly enriched vimentin, a dedifferentiation and pro-metastatic marker, induced by KLF6-SV1. c-MYC-positive tumors were also significantly enriched for KLF6-SV1 in human prostate cancer specimens. Our findings provide evidence that KLF6-SV1 is an enhancer of c-MYC-driven prostate cancer progression and metastasis, and a correlated genetic event in human prostate cancer with potential translational significance.

Applications of artificial intelligence in prostate cancer histopathology.

The diagnosis of prostate cancer (PCa) depends on the evaluation of core needle biopsies by trained pathologists. Artificial intelligence (AI) derived models have been created to address the challenges posed by pathologists' increasing workload, workforce shortages, and variability in histopathology assessment. These models with histopathological parameters integrated into sophisticated neural networks demonstrate remarkable ability to identify, grade, and predict outcomes for PCa. Though the fully autonomous diagnosis of PCa remains elusive, recently published data suggests that AI has begun to serve as an initial screening tool, an assistant in the form of a real-time interactive interface during histological analysis, and as a second read system to detect false negative diagnoses. Our article aims to describe recent advances and future opportunities for AI in PCa histopathology.

Cellular mechanisms associated with sub-optimal immune responses to SARS-CoV-2 bivalent booster vaccination in patients with Multiple Myeloma.

BACKGROUND: The real-world impact of bivalent vaccines for wild type (WA.1) and Omicron variant (BA.5) is largely unknown in immunocompromised patients with Multiple Myeloma (MM). We characterize the humoral and cellular immune responses in patients with MM before and after receiving the bivalent booster, including neutralizing assays to identify patterns associated with continuing vulnerability to current variants (XBB1.16, EG5) in the current post-pandemic era. METHODS: We studied the humoral and cellular immune responses before and after bivalent booster immunization in 48 MM patients. Spike binding IgG antibody levels were measured by SARS-CoV-2 spike binding ELISA and neutralization capacity was assessed by a SARS-CoV-2 multi-cycle microneutralization assays to assess inhibition of live virus. We measured spike specific T-cell function using the QuantiFERON SARS-CoV-2 (Qiagen) assay as well as flow-cytometry based T-cell. In a subset of 38 patients, high-dimensional flow cytometry was performed to identify immune cell subsets associated with lack of humoral antibodies. FINDINGS: We find that bivalent vaccination provides significant boost in protection to the omicron variant in our MM patients, in a treatment specific manner. MM patients remain vulnerable to newer variants with mutations in the spike portion. Anti-CD38 and anti-BCMA therapies affect the immune machinery needed to produce antibodies. INTERPRETATION: Our study highlights varying immune responses observed in MM patients after receiving bivalent COVID-19 vaccination. Specifically, a subgroup of MM patients undergoing anti-CD38 and anti-BCMA therapy experience impairment in immune cells such DCs, B cells, NK cells and TFH cells, leading to an inability to generate adequate humoral and cellular responses to vaccination. FUNDING: National Cancer Institute (National Institutes of Health), National Institute of Allergy and Infectious Diseases (National Institutes of Health), NCI Serological Sciences Network for COVID-19 (SeroNet) and The Icahn School of Medicine at Mount Sinai.

Master Transcription Factor Reprogramming Unleashes Selective Translation Promoting Castration Resistance and Immune Evasion in Lethal Prostate Cancer.

Signaling rewiring allows tumors to survive therapy. Here we show that the decrease of the master regulator microphthalmia transcription factor (MITF) in lethal prostate cancer unleashes eukaryotic initiation factor 3B (eIF3B)-dependent translation reprogramming of key mRNAs conferring resistance to androgen deprivation therapy (ADT) and promoting immune evasion. Mechanistically, MITF represses through direct promoter binding eIF3B, which in turn regulates the translation of specific mRNAs. Genome-wide eIF3B enhanced cross-linking immunoprecipitation sequencing (eCLIP-seq) showed specialized binding to a UC-rich motif present in subsets of 5' untranslated regions. Indeed, translation of the androgen receptor and major histocompatibility complex I (MHC-I) through this motif is sensitive to eIF3B amount. Notably, pharmacologic targeting of eIF3B-dependent translation in preclinical models sensitizes prostate cancer to ADT and anti-PD-1 therapy. These findings uncover a hidden connection between transcriptional and translational rewiring promoting therapy-refractory lethal prostate cancer and provide a druggable mechanism that may transcend into effective combined therapeutic strategies. SIGNIFICANCE: Our study shows that specialized eIF3B-dependent translation of specific mRNAs released upon downregulation of the master transcription factor MITF confers castration resistance and immune evasion in lethal prostate cancer. Pharmacologic targeting of this mechanism delays castration resistance and increases immune-checkpoint efficacy. This article is featured in Selected Articles from This Issue, p. 2489.

The DACH1 gene is frequently deleted in prostate cancer, restrains prostatic intraepithelial neoplasia, decreases DNA damage repair, and predicts therapy responses.

Prostate cancer (PCa), the second leading cause of death in American men, includes distinct genetic subtypes with distinct therapeutic vulnerabilities. The DACH1 gene encodes a winged helix/Forkhead DNA-binding protein that competes for binding to FOXM1 sites. Herein, DACH1 gene deletion within the 13q21.31-q21.33 region occurs in up to 18% of human PCa and was associated with increased AR activity and poor prognosis. In prostate OncoMice, prostate-specific deletion of the Dach1 gene enhanced prostatic intraepithelial neoplasia (PIN), and was associated with increased TGFß activity and DNA damage. Reduced Dach1 increased DNA damage in response to genotoxic stresses. DACH1 was recruited to sites of DNA damage, augmenting recruitment of Ku70/Ku80. Reduced Dach1 expression was associated with increased homology directed repair and resistance to PARP inhibitors and TGFß kinase inhibitors. Reduced Dach1 expression may define a subclass of PCa that warrants specific therapies.

Harnessing transcriptionally driven chromosomal instability adaptation to target therapy-refractory lethal prostate cancer.

Metastatic prostate cancer (PCa) inevitably acquires resistance to standard therapy preceding lethality. Here, we unveil a chromosomal instability (CIN) tolerance mechanism as a therapeutic vulnerability of therapy-refractory lethal PCa. Through genomic and transcriptomic analysis of patient datasets, we find that castration and chemotherapy-resistant tumors display the highest CIN and mitotic kinase levels. Functional genomics screening coupled with quantitative phosphoproteomics identify MASTL kinase as a survival vulnerability specific of chemotherapy-resistant PCa cells. Mechanistically, MASTL upregulation is driven by transcriptional rewiring mechanisms involving the non-canonical transcription factors androgen receptor splice variant 7 and E2F7 in a circuitry that restrains deleterious CIN and prevents cell death selectively in metastatic therapy-resistant PCa cells. Notably, MASTL pharmacological inhibition re-sensitizes tumors to standard therapy and improves survival of pre-clinical models. These results uncover a targetable mechanism promoting high CIN adaptation and survival of lethal PCa.

The DACH1 gene is frequently deleted in prostate cancer, restrains prostatic intraepithelial neoplasia, decreases DNA damage repair, and predicts therapy responses.

Prostate cancer (PCa), the second leading cause of death in American men, includes distinct genetic subtypes with distinct therapeutic vulnerabilities. The DACH1 gene encodes a winged helix/Forkhead DNA-binding protein that competes for binding to FOXM1 sites. Herein, DACH1 gene deletion within the 13q21.31-q21.33 region occurs in up to 18% of human PCa and was associated with increased AR activity and poor prognosis. In prostate OncoMice, prostate-specific deletion of the Dach1 gene enhanced prostatic intraepithelial neoplasia (PIN), and was associated with increased TGFb activity and DNA damage. Reduced Dach1 increased DNA damage in response to genotoxic stresses. DACH1 was recruited to sites of DNA damage, augmenting recruitment of Ku70/Ku80. Reduced Dach1 expression was associated with increased homology directed repair and resistance to PARP inhibitors and TGFb kinase inhibitors. Reduced Dach1 expression may define a subclass of PCa that warrants specific therapies.

Development and characterization of a new monoclonal antibody against SARS-CoV-2 NSP12 (RdRp).

SARS-CoV-2 NSP12, the viral RNA-dependent RNA polymerase (RdRp), is required for viral replication and is a therapeutic target to treat COVID-19. To facilitate research on SARS-CoV-2 NSP12 protein, we developed a rat monoclonal antibody (CM12.1) against the NSP12 N-terminus that can facilitate functional studies. Immunoblotting and immunofluorescence assay (IFA) confirmed the specific detection of NSP12 protein by this antibody for cells overexpressing the protein. Although NSP12 is generated from the ORF1ab polyprotein, IFA of human autopsy COVID-19 lung samples revealed NSP12 expression in only a small fraction of lung cells including goblet, club-like, vascular endothelial cells, and a range of immune cells, despite wide-spread tissue expression of spike protein antigen. Similar studies using in vitro infection also generated scant protein detection in cells with established virus replication. These results suggest that NSP12 may have diminished steady-state expression or extensive posttranslation modifications that limit antibody reactivity during SARS-CoV-2 replication.

Development and validation of an AI-enabled digital breast cancer assay to predict early-stage breast cancer recurrence within 6 years.

BACKGROUND: Breast cancer (BC) grading plays a critical role in patient management despite the considerable inter- and intra-observer variability, highlighting the need for decision support tools to improve reproducibility and prognostic accuracy for use in clinical practice. The objective was to evaluate the ability of a digital artificial intelligence (AI) assay (PDxBr) to enrich BC grading and improve risk categorization for predicting recurrence. METHODS: In our population-based longitudinal clinical development and validation study, we enrolled 2075 patients from Mount Sinai Hospital with infiltrating ductal carcinoma of the breast. With 3:1 balanced training and validation cohorts, patients were retrospectively followed for a median of 6 years. The main outcome was to validate an automated BC phenotyping system combined with clinical features to produce a binomial risk score predicting BC recurrence at diagnosis. RESULTS: The PDxBr training model (n = 1559 patients) had a C-index of 0.78 (95% CI, 0.76-0.81) versus clinical 0.71 (95% CI, 0.67-0.74) and image feature models 0.72 (95% CI, 0.70-0.74). A risk score of 58 (scale 0-100) stratified patients as low or high risk, hazard ratio (HR) 5.5 (95% CI 4.19-7.2, p < 0.001), with a sensitivity 0.71, specificity 0.77, NPV 0.95, and PPV 0.32 for predicting BC recurrence within 6 years. In the validation cohort (n = 516), the C-index was 0.75 (95% CI, 0.72-0.79) versus clinical 0.71 (95% CI 0.66-0.75) versus image feature models 0.67 (95% CI, 0.63-071). The validation cohort had an HR of 4.4 (95% CI 2.7-7.1, p < 0.001), sensitivity of 0.60, specificity 0.77, NPV 0.94, and PPV 0.24 for predicting BC recurrence within 6 years. PDxBr also improved Oncotype Recurrence Score (RS) performance: RS 31 cutoff, C-index of 0.36 (95% CI 0.26-0.45), sensitivity 37%, specificity 48%, HR 0.48, p = 0.04 versus Oncotype RS plus AI-grade C-index 0.72 (95% CI 0.67-0.79), sensitivity 78%, specificity 49%, HR 4.6, p < 0.001 versus Oncotype RS plus PDxBr, C-index 0.76 (95% CI 0.70-0.82), sensitivity 67%, specificity 80%, HR 6.1, p < 0.001. CONCLUSIONS: PDxBr is a digital BC test combining automated AI-BC prognostic grade with clinical-pathologic features to predict the risk of early-stage BC recurrence. With future validation studies, we anticipate the PDxBr model will enrich current gene expression assays and enhance treatment decision-making.

circCsnk1g3- and circAnkib1-regulated interferon responses in sarcoma promote tumorigenesis by shaping the immune microenvironment.

Exonic circular RNAs (circRNAs) produce predominantly non-coding RNA species that have been recently profiled in many tumors. However, their functional contribution to cancer progression is still poorly understood. Here, we identify the circRNAs expressed in soft tissue sarcoma cells and explore how the circRNAs regulate sarcoma growth in vivo. We show that circCsnk1g3 and circAnkib1 promote tumor growth by shaping a pro-tumorigenic microenvironment, possibly due to their capabilities to regulate tumor-promoting elements extrinsic to the tumor cells. Accordingly, circCsnk1g3 and circAnkib1 can control the expression of interferon-related genes and pro-inflammatory factors in the sarcoma cells, thus directing immune cell recruitment into the tumor mass, and hence their activation. Mechanistically, circRNAs may repress pro-inflammatory elements by buffering activation of the pathways mediated by RIG-I, the cytosolic viral RNA sensor. The current findings suggest that the targeting of specific circRNAs could augment the efficacy of tumor and immune response to mainstay therapies.

Association between Incidental Pelvic Inflammation and Aggressive Prostate Cancer.

The impact of pelvic inflammation on prostate cancer (PCa) biology and aggressive phenotype has never been studied. Our study objective was to evaluate the role of pelvic inflammation on PCa aggressiveness and its association with clinical outcomes in patients following radical prostatectomy (RP). This study has been conducted on a retrospective single-institutional consecutive cohort of 2278 patients who underwent robot-assisted laparoscopic prostatectomy (RALP) between 01/2013 and 10/2019. Data from 2085 patients were analyzed to study the association between pelvic inflammation and adverse pathology (AP), defined as Gleason Grade Group (GGG) > 2 and ≥ pT3 stage, at resection. In a subset of 1997 patients, the association between pelvic inflammation and biochemical recurrence (BCR) was studied. Alteration in tumor transcriptome and inflammatory markers in patients with and without pelvic inflammation were studied using microarray analysis, immunohistochemistry, and culture supernatants derived from inflamed sites used in functional assays. Changes in blood inflammatory markers in the study cohort were analyzed by O-link. In univariate analyses, pelvic inflammation emerged as a significant predictor of AP. Multivariate cox proportional-hazards regression analyses showed that high pelvic inflammation with pT3 stage and positive surgical margins significantly affected the time to BCR (p ≤ 0.05). PCa patients with high inflammation had elevated levels of pro-inflammatory cytokines in their tissues and in blood. Genes involved in epithelial-to-mesenchymal transition (EMT) and DNA damage response were upregulated in patients with pelvic inflammation. Attenuation of STAT and IL-6 signaling decreased tumor driving properties of conditioned medium from inflamed sites. Pelvic inflammation exacerbates the progression of prostate cancer and drives an aggressive phenotype.

Extracellular vesicles carry distinct proteo-transcriptomic signatures that are different from their cancer cell of origin.

Circulating extracellular vesicles (EVs) contain molecular footprints-lipids, proteins, RNA, and DNA-from their cell of origin. Consequently, EV-associated RNA and proteins have gained widespread interest as liquid-biopsy biomarkers. Yet, an integrative proteo-transcriptomic landscape of EVs and comparison with their cell of origin remains obscure. Here, we report that EVs enrich distinct proteo-transcriptome that does not linearly correlate with their cell of origin. We show that EVs enrich endosomal and extracellular proteins, small RNA (∼13-200 nucleotides) associated with cell differentiation, development, and Wnt signaling. EVs cargo specific RNAs (RNY3, vtRNA, and MIRLET-7) and their complementary proteins (YBX1, IGF2BP2, and SRSF1/2). To ensure an unbiased and independent analyses, we studied 12 cancer cell lines, matching EVs (inhouse and exRNA database), and serum EVs of patients with prostate cancer. Together, we show that EV-RNA-protein complexes may constitute a functional interaction network to protect and regulate molecular access until a function is achieved.

The Serological Sciences Network (SeroNet) for COVID-19: Depth and Breadth of Serology Assays and Plans for Assay Harmonization.

In October 2020, the National Cancer Institute (NCI) Serological Sciences Network (SeroNet) was established to study the immune response to COVID-19, and "to develop, validate, improve, and implement serological testing and associated technologies" (https://www.cancer.gov/research/key-initiatives/covid-19/coronavirus-research-initiatives/serological-sciences-network). SeroNet is comprised of 25 participating research institutions partnering with the Frederick National Laboratory for Cancer Research (FNLCR) and the SeroNet Coordinating Center. Since its inception, SeroNet has supported collaborative development and sharing of COVID-19 serological assay procedures and has set forth plans for assay harmonization. To facilitate collaboration and procedure sharing, a detailed survey was sent to collate comprehensive assay details and performance metrics on COVID-19 serological assays within SeroNet. In addition, FNLCR established a protocol to calibrate SeroNet serological assays to reference standards, such as the U.S. severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serology standard reference material and first WHO international standard (IS) for anti-SARS-CoV-2 immunoglobulin (20/136), to facilitate harmonization of assay reporting units and cross-comparison of study data. SeroNet institutions reported development of a total of 27 enzyme-linked immunosorbent assay (ELISA) methods, 13 multiplex assays, and 9 neutralization assays and use of 12 different commercial serological methods. FNLCR developed a standardized protocol for SeroNet institutions to calibrate these diverse serological assays to reference standards. In conclusion, SeroNet institutions have established a diverse array of COVID-19 serological assays to study the immune response to SARS-CoV-2 and vaccines. Calibration of SeroNet serological assays to harmonize results reporting will facilitate future pooled data analyses and study cross-comparisons. IMPORTANCE SeroNet institutions have developed or implemented 61 diverse COVID-19 serological assays and are collaboratively working to harmonize these assays using reference materials to establish standardized reporting units. This will facilitate clinical interpretation of serology results and cross-comparison of research data.

The Serological Sciences Network (SeroNet) for COVID-19: Depth and Breadth of Serology Assays and Plans for Assay Harmonization.

Background: In October 2020, the National Cancer Institute (NCI) Serological Sciences Network (SeroNet) was established to study the immune response to COVID-19, and "to develop, validate, improve, and implement serological testing and associated technologies." SeroNet is comprised of 25 participating research institutions partnering with the Frederick National Laboratory for Cancer Research (FNLCR) and the SeroNet Coordinating Center. Since its inception, SeroNet has supported collaborative development and sharing of COVID-19 serological assay procedures and has set forth plans for assay harmonization. Methods: To facilitate collaboration and procedure sharing, a detailed survey was sent to collate comprehensive assay details and performance metrics on COVID-19 serological assays within SeroNet. In addition, FNLCR established a protocol to calibrate SeroNet serological assays to reference standards, such as the U.S. SARS-CoV-2 serology standard reference material and First WHO International Standard (IS) for anti-SARS-CoV-2 immunoglobulin (20/136), to facilitate harmonization of assay reporting units and cross-comparison of study data. Results: SeroNet institutions reported development of a total of 27 ELISA methods, 13 multiplex assays, 9 neutralization assays, and use of 12 different commercial serological methods. FNLCR developed a standardized protocol for SeroNet institutions to calibrate these diverse serological assays to reference standards. Conclusions: SeroNet institutions have established a diverse array of COVID-19 serological assays to study the immune response to SARS-CoV-2 virus and vaccines. Calibration of SeroNet serological assays to harmonize results reporting will facilitate future pooled data analyses and study cross-comparisons.

Antemortem detection of Parkinson's disease pathology in peripheral biopsies using artificial intelligence.

The diagnosis of Parkinson's disease (PD) is challenging at all stages due to variable symptomatology, comorbidities, and mimicking conditions. Postmortem assessment remains the gold standard for a definitive diagnosis. While it is well recognized that PD manifests pathologically in the central nervous system with aggregation of α-synuclein as Lewy bodies and neurites, similar Lewy-type synucleinopathy (LTS) is additionally found in the peripheral nervous system that may be useful as an antemortem biomarker. We have previously found that detection of LTS in submandibular gland (SMG) biopsies is sensitive and specific for advanced PD; however, the sensitivity is suboptimal especially for early-stage disease. Further, visual microscopic assessment of biopsies by a neuropathologist to identify LTS is impractical for large-scale adoption. Here, we trained and validated a convolutional neural network (CNN) for detection of LTS on 283 digital whole slide images (WSI) from 95 unique SMG biopsies. A total of 8,450 LTS and 35,066 background objects were annotated following an inter-rater reliability study with Fleiss Kappa = 0.72. We used transfer learning to train a CNN model to classify image patches (151 × 151 pixels at 20× magnification) with and without the presence of LTS objects. The trained CNN model showed the following performance on image patches: sensitivity: 0.99, specificity: 0.99, precision: 0.81, accuracy: 0.99, and F-1 score: 0.89. We further tested the trained network on 1230 naïve WSI from the same cohort of research subjects comprising 42 PD patients and 14 controls. Logistic regression models trained on features engineered from the CNN predictions on the WSI resulted in sensitivity: 0.71, specificity: 0.65, precision: 0.86, accuracy: 0.69, and F-1 score: 0.76 in predicting clinical PD status, and 0.64 accuracy in predicting PD stage, outperforming expert neuropathologist LTS density scoring in terms of sensitivity but not specificity. These findings demonstrate the practical utility of a CNN detector in screening for LTS, which can translate into a computational tool to facilitate the antemortem tissue-based diagnosis of PD in clinical settings.

MicroRNA-21 deficiency suppresses prostate cancer progression through downregulation of the IRS1-SREBP-1 signaling pathway.

Sterol regulatory element-binding protein 1 (SREBP-1), a master transcription factor in lipogenesis and lipid metabolism, is critical for disease progression and associated with poor outcomes in prostate cancer (PCa) patients. However, the mechanism of SREBP-1 regulation in PCa remains elusive. Here, we report that SREBP-1 is transcriptionally regulated by microRNA-21 (miR-21) in vitro in cultured cells and in vivo in mouse models. We observed aberrant upregulation of SREBP-1, fatty acid synthase (FASN) and acetyl-CoA carboxylase (ACC) in Pten/Trp53 double-null mouse embryonic fibroblasts (MEFs) and Pten/Trp53 double-null mutant mice. Strikingly, miR-21 loss significantly reduced cell proliferation and suppressed the prostate tumorigenesis of Pten/Trp53 mutant mice. Mechanistically, miR-21 inactivation decreased the levels of SREBP-1, FASN, and ACC in human PCa cells through downregulation of insulin receptor substrate 1 (IRS1)-mediated transcription and induction of cellular senescence. Conversely, miR-21 overexpression increased cell proliferation and migration; as well as the levels of IRS1, SREBP-1, FASN, and ACC in human PCa cells. Our findings reveal that miR-21 promotes PCa progression by activating the IRS1/SREBP-1 axis, and targeting miR-21/SREBP-1 signaling pathway can be a novel strategy for controlling PCa malignancy.

Robust clinical detection of SARS-CoV-2 variants by RT-PCR/MALDI-TOF multitarget approach.

The coronavirus disease 2019 (COVID-19) pandemic has sparked the rapid development of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnostics. However, emerging variants pose the risk for target dropout and false-negative results secondary to primer/probe binding site (PBS) mismatches. The Agena MassARRAY® SARS-CoV-2 Panel combines reverse-transcription polymerase chain reaction and matrix-assisted laser desorption/ionization time-of-flight mass-spectrometry to probe for five targets across N and ORF1ab genes, which provides a robust platform to accommodate PBS mismatches in divergent viruses. Herein, we utilize a deidentified data set of 1262 SARS-CoV-2-positive specimens from Mount Sinai Health System (New York City) from December 2020 to April 2021 to evaluate target results and corresponding sequencing data. Overall, the level of PBS mismatches was greater in specimens with target dropout. Of specimens with N3 target dropout, 57% harbored an A28095T substitution that is highly specific for the Alpha (B.1.1.7) variant of concern. These data highlight the benefit of redundancy in target design and the potential for target performance to illuminate the dynamics of circulating SARS-CoV-2 variants.

The Evolving Clinical Management of Genitourinary Cancers Amid the COVID-19 Pandemic.

Coronavirus disease-2019 (COVID-19), a disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection, has become an unprecedented global health emergency, with fatal outcomes among adults of all ages throughout the world. There is a high incidence of infection and mortality among cancer patients with evidence to support that patients diagnosed with cancer and SARS-CoV-2 have an increased likelihood of a poor outcome. Clinically relevant changes imposed as a result of the pandemic, are either primary, due to changes in timing or therapeutic modality; or secondary, due to altered cooperative effects on disease progression or therapeutic outcomes. However, studies on the clinical management of patients with genitourinary cancers during the COVID-19 pandemic are limited and do little to differentiate primary or secondary impacts of COVID-19. Here, we provide a review of the epidemiology and biological consequences of SARS-CoV-2 infection in GU cancer patients as well as the impact of COVID-19 on the diagnosis and management of these patients, and the use and development of novel and innovative diagnostic tests, therapies, and technology. This article also discusses the biomedical advances to control the virus and evolving challenges in the management of prostate, bladder, kidney, testicular, and penile cancers at all stages of the patient journey during the first year of the COVID-19 pandemic.