Citations

AbstractAlthough cancer is highly heterogeneous, all metastatic cancer is considered American Joint Committee on Cancer (AJCC) Stage IV disease. The purpose of this project was to redefine staging of metastatic cancer. Internal validation of nationally representative patient data from the National Cancer Database (n = 461 357; 2010‐2013), and external validation using the Surveillance, Epidemiology and End Results database (n = 106 595; 2014‐2015) were assessed using the concordance index for evaluation of survival prediction. A Cox proportional hazards model was used for overall survival by considering identified phenotypes (latent classes) and other confounding variables. Latent class analysis was performed for phenotype identification, where Bayesian information criterion (BIC) and sample‐size‐adjusted BIC were used to select the optimal number of distinct clusters. Kappa coefficients assessed external cluster validation. Latent class analysis identified five metastatic phenotypes with differences in overall survival (P < .0001): (Stage IVA) nearly exclusive bone‐only metastases (n = 59 049, 12.8%; median survival 12.7 months; common in lung, breast and prostate cancers); (IVB) predominant lung metastases (n = 62 491, 13.5%; 11.4 months; common in breast, stomach, kidney, ovary, uterus, thyroid, cervix and soft tissue cancers); (IVC) predominant liver/lung metastases (n = 130 014, 28.2%; 7.0 months; common in colorectum, pancreatic, lung, esophagus and stomach cancers); (IVD) bone/liver/lung metastases predominant over brain (n = 61 004, 13.2%; 5.9 months; common in lung and breast cancers); and (IVE) brain/lung metastases predominant over bone/liver (n = 148 799, 32.3%; 5.7 months; lung cancer and melanoma). Long‐term survivors were identified, particularly in Stages IVA‐B. A pan‐cancer nomogram model to predict survival (STARS: site, tumor, age, race, sex) was created, validated and provides 13% better prognostication than AJCC: 1‐month concordance index of 0.67 (95% confidence interval [CI]: 0.66‐0.67) vs 0.61 (95% CI: 0.60‐0.61). STARS is simple, uses easily accessible variables, better prognosticates survival outcomes and provides a platform to develop novel metastasis‐directed clinical trials.

Abstract In patients with transplant-ineligible newly diagnosed multiple myeloma (NDMM), daratumumab reduced the risk of disease progression or death by 44% in MAIA (daratumumab/lenalidomide/dexamethasone [D-Rd]) and 58% in ALCYONE (daratumumab/bortezomib/melphalan/prednisone [D-VMP]). Minimal residual disease (MRD) is a sensitive measure of disease and response to therapy. MRD-negativity status and durability were assessed in MAIA and ALCYONE. MRD assessments using next-generation sequencing (10−5) occurred for patients achieving complete response (CR) or better and after at least CR at 12, 18, 24, and 30 months from the first dose. Progression-free survival (PFS) by MRD status and sustained MRD negativity lasting ≥6 and ≥12 months were analyzed in the intent-to-treat population and among patients achieving at least CR. In MAIA (D-Rd, n = 368; lenalidomide and dexamethasone [Rd], n = 369) and ALCYONE (D-VMP, n = 350; bortezomib/melphalan/prednisone [VMP], n = 356), the median duration of follow-up was 36.4 and 40.1 months, respectively. MRD-negative status and sustained MRD negativity lasting ≥6 and ≥12 months were associated with improved PFS, regardless of treatment group. However, daratumumab-based therapy improved rates of MRD negativity lasting ≥6 months (D-Rd, 14.9% vs Rd, 4.3%; D-VMP, 15.7% vs VMP, 4.5%) and ≥12 months (D-Rd, 10.9% vs Rd, 2.4%; D-VMP, 14.0% vs VMP, 2.8%), both of which translated to improved PFS vs control groups. In a pooled analysis, patients who were MRD negative had improved PFS vs patients who were MRD positive. Patients with NDMM who achieved MRD-negative status or sustained MRD negativity had deep remission and improved clinical outcomes. These trials were registered at www.clinicaltrials.gov as #NCT02252172 (MAIA) and #NCT02195479 (ALCYONE).

AbstractIntroductionThe efficacy of cardiac resynchronization therapy (CRT) has been widely studied in the medical literature; however, about 30% of candidates fail to respond to this treatment strategy. Smart computational approaches based on clinical data can help expose hidden patterns useful for identifying CRT responders.MethodsWe retrospectively analyzed the electronic health records of 1664 patients who underwent CRT procedures from January 1, 2002 to December 31, 2017. An ensemble of ensemble (EoE) machine learning (ML) system composed of a supervised and an unsupervised ML layers was developed to generate a prediction model for CRT response.ResultsWe compared the performance of EoE against traditional ML methods and the state‐of‐the‐art convolutional neural network (CNN) model trained on raw electrocardiographic (ECG) waveforms. We observed that the models exhibited improvement in performance as more features were incrementally used for training. Using the most comprehensive set of predictors, the performance of the EoE model in terms of the area under the receiver operating characteristic curve and F1‐score were 0.76 and 0.73, respectively. Direct application of the CNN model on the raw ECG waveforms did not generate promising results.ConclusionThe proposed CRT risk calculator effectively discriminates which heart failure (HF) patient is likely to respond to CRT significantly better than using clinical guidelines and traditional ML methods, thus suggesting that the tool can enhanced care management of HF patients by helping to identify high‐risk patients.

Abstract Acquired PARP inhibitor (PARPi) resistance in BRCA1- or BRCA2-mutant ovarian cancer often results from secondary mutations that restore expression of functional protein. RAD51C is a less commonly studied ovarian cancer susceptibility gene whose promoter is sometimes methylated, leading to homologous recombination (HR) deficiency and PARPi sensitivity. For this study, the PARPi-sensitive patient-derived ovarian cancer xenograft PH039, which lacks HR gene mutations but harbors RAD51C promoter methylation, was selected for PARPi resistance by cyclical niraparib treatment in vivo. PH039 acquired PARPi resistance by the third treatment cycle and grew through subsequent treatment with either niraparib or rucaparib. Transcriptional profiling throughout the course of resistance development showed widespread pathway level changes along with a marked increase in RAD51C mRNA, which reflected loss of RAD51C promoter methylation. Analysis of ovarian cancer samples from the ARIEL2 Part 1 clinical trial of rucaparib monotherapy likewise indicated an association between loss of RAD51C methylation prior to on-study biopsy and limited response. Interestingly, the PARPi resistant PH039 model remained platinum sensitive. Collectively, these results not only indicate that PARPi treatment pressure can reverse RAD51C methylation and restore RAD51C expression, but also provide a model for studying the clinical observation that PARPi and platinum sensitivity are sometimes dissociated.

Background . Patients increasingly use asynchronous communication platforms to converse with care teams. Natural language processing (NLP) to classify content and automate triage of these messages has great potential to enhance clinical efficiency. We characterize the contents of a corpus of portal messages generated by patients using NLP methods. We aim to demonstrate descriptive analyses of patient text that can contribute to the development of future sophisticated NLP applications. Methods . We collected approximately 3,000 portal messages from the cardiology, dermatology, and gastroenterology departments at Mayo Clinic. After labeling these messages as either Active Symptom, Logistical, Prescription, or Update, we used NER (named entity recognition) to identify medical concepts based on the UMLS library. We hierarchically analyzed the distribution of these messages in terms of departments, message types, medical concepts, and keywords therewithin. Results . Active Symptom and Logistical content types comprised approximately 67% of the message cohort. The “Findings” medical concept had the largest number of keywords across all groupings of content types and departments. “Anatomical Sites” and “Disorders” keywords were more prevalent in Active Symptom messages, while “Drugs” keywords were most prevalent in Prescription messages. Logistical messages tended to have the lower proportions of “Anatomical Sites,”, “Disorders,”, “Drugs,”, and “Findings” keywords when compared to other message content types. Conclusions . This descriptive corpus analysis sheds light on the content and foci of portal messages. The insight into the content and differences among message themes can inform the development of more robust NLP models.

Introduction: Senescent cells with essentially irreversible loss of replicative potential accumulate in various tissues with aging. Cellular senescence is associated with a pro‐inflammatory senescence‐associated secretory phenotype which the Janus‐associated kinase (JAK) pathway plays a role in. We hypothesized that senescent preadipocytes contribute to age‐related dysfunction of healthy cells. Methods: Preadipocytes from lean subjects were X‐irradiated to induce senescence. We co‐cultured non‐senescent cells with senescent cells or cultured them in conditioned medium (CM) from senescent preadipocytes to test the inflammation, differentiation and insulin sensitivity. Macrophage migration in response to CM was assayed as well. Moreover, we treated old or obese mice with Ruxolitinib, a JAK1/2 inhibitor, to test the beneficial effect. Results: The adipogenesis of preadipocytes was impaired by exposure to senescent cells. Macrophage migration was greater in response to senescent preadipocytes. Inflammation was increased in both adipose tissue and preadipocytes exposed to CM from senescent cells. All these adverse effect could be partially rescued by JAK inhibitor. In addition, senescent preadipocytes inhibited insulin‐induced phosphor‐AKT in adipose tissue and HepG2 cells. Insulin‐induced glycogen synthesis was also inhibited in HepG2 cells. Two months of Ruxolitinib treatment reduced inflammation, reversed age‐related lipodystrophy and improved physical function in frail, 24 month old mice. It also improved insulin sensitivity in diet‐induced obese mice. Conclusion: Senescent preadipocytes contribute to age‐related impairment in adipogenesis, fat tissue inflammation, and insulin resistance. Grant Funding Source : supported by NIH AG13925 and Robert and Arlene Kogod Center on Aging in Mayo Clinic.

Niclosamide is a salicylanilide derivative used as antihelminthic agent. Recently, Nic has been screened out as an autophagy modulator by us and other groups and was identified to be a structurally distinct mTORC1 signaling inhibitor. In this work, we measured the long‐lived protein degradation activity and found Niclosamide could inhibit the autophagic process. To elucidate the inhibition of Niclosamide on autophagy, we further tested the lysosomal activity using DQ‐BSA assay and measured protease activity such as Cathepsin B and Cathepsin D with fluorescent substrates. The lower degradation of DQ‐BSA and decreased protease activity after Niclosamide treatments indicated the impaired lysosome function. In addition, both LC‐II and P62 proteins accumulated significantly when treated by Niclosamide suggesting the late stage of autophagy was blocked. The increased pH of lysosome and release of Cathepsins from lysosome to cytosol demonstrated that Niclosamide might affect lysosome resulted from lysosomal membrane permeabilization. Collectively, we firstly disclosed Niclosamide not only inhibited mTORC1 activity but also, as other well‐known lysosome inhibitors, strongly blocked autophagy via lysosomal dysfunction. Grant Funding Source : Supported by Guandong Provincial Natural Science Foundation, China (S2013010015876)

The Genitourinary Pathology Society (GUPS) undertook a critical review of the recent advances in bladder cancer focusing on important topics of high interest for the practicing surgical pathologist and urologist. This review represents the second of 2 manuscripts ensuing from this effort. Herein, we address the effective reporting of bladder cancer, focusing particularly on newly published data since the last 2016 World Health Organization (WHO) classification. In addition, this review focuses on the importance of reporting bladder cancer with divergent differentiation and variant (subtypes of urothelial carcinoma) histologies and the potential impact on patient care. We provide new recommendations for reporting pT1 staging in diagnostic pathology. Furthermore, we explore molecular evolution and classification, emphasizing aspects that impact the understanding of important concepts relevant to reporting and management of patients.

The Genitourinary Pathology Society (GUPS) undertook a critical review of the recent advances in bladder neoplasia with a focus on issues relevant to the practicing surgical pathologist for the understanding and effective reporting of bladder cancer, emphasizing particularly on the newly accumulated evidence post-2016 World Health Organization (WHO) classification. The work is presented in 2 manuscripts. Here, in the first, we revisit the nomenclature and classification system used for grading flat and papillary urothelial lesions centering on clinical relevance, and on dilemmas related to application in routine reporting. As patients of noninvasive bladder cancer frequently undergo cystoscopy and biopsy in their typically prolonged clinical course and for surveillance of disease, we discuss morphologies presented in these scenarios which may not have readily applicable diagnostic terms in the WHO classification. The topic of inverted patterns in urothelial neoplasia, particularly when prominent or exclusive, and beyond inverted papilloma has not been addressed formally in the WHO classification. Herein we provide a through review and suggest guidelines for when and how to report such lesions. In promulgating these GUPS recommendations, we aim to provide clarity on the clinical application of these not so uncommon diagnostically challenging situations encountered in routine practice, while also importantly advocating consistent terminology which would inform future work.

Abstract Objectives To demonstrate clinicopathologic features and evaluate the clonality of double PIK3CA alterations in colorectal cancers (CRCs). Methods Clonality was examined in 13 CRCs with double PIK3CA alterations (1.7% of CRCs or 9.6% of PIK3CA-mutated CRCs). Multiregional analyses were performed to confirm subclonal PIK3CA alterations. Results PIK3CA alterations were detected within exon 9 (51%), exon 20 (23%), exon 1 (15%), and exon 7 (6.0%). CRCs with exon 7 alterations showed a significantly higher incidence of double PIK3CA alterations. Most double PIK3CA alterations consisted of a hotpsot alteration and an uncommon alteration; they were often clonal and present within a single tumor population. Multiregional analyses of CRCs with predicted subclonal double-alterations revealed multiclonal CRCs with divergent PIK3CA variant status originating from a common APC- and KRAS-mutated founder lineage of adenoma. Conclusions The findings supported multiclonal CRCs resulting from parallel evolution during the progression from adenoma to adenocarcinoma within the mitogen-activated protein kinase pathway, as previously demonstrated, or the mammalian target of rapamycin pathway. Further studies are warranted to elucidate clinical significance and potential targeted therapy for CRC patients with double PIK3CA alterations and impacts on clinical decision-making in patients with multiclonal CRCs harboring divergent PIK3CA mutational status.