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Cancer cells shed naked DNA molecules into the circulation. This circulating tumor DNA (ctDNA) has become the predominant analyte for liquid biopsies to understand the mutational landscape of cancer. Coupled with next-generation sequencing, ctDNA can serve as an alternative substrate to tumor tissues for mutation detection and companion diagnostic purposes. In fact, recent advances in precision medicine have rapidly enabled the use of ctDNA to guide treatment decisions for predicting response and resistance to targeted therapies and immunotherapies. An advantage of using ctDNA over conventional tissue biopsies is the relatively noninvasive approach of obtaining peripheral blood, allowing for simple repeated and serial assessments. Most current clinical practice using ctDNA has endeavored to identify druggable and resistance mutations for guiding systemic therapy decisions, albeit mostly in metastatic disease. However, newer research is evaluating potential for ctDNA as a marker of minimal residual disease in the curative setting and as a useful screening tool to detect cancer in the general population. Here we review the history of ctDNA and liquid biopsies, technologies to detect ctDNA, and some of the current challenges and limitations in using ctDNA as a marker of minimal residual disease and as a general blood-based cancer screening tool. We also discuss the need to develop rigorous clinical studies to prove the clinical utility of ctDNA for future applications in oncology.

Genomic sequencing of thousands of tumors has revealed many genes associated with specific types of cancer. Similarly, large scale CRISPR functional genomics efforts have mapped genes required for cancer cell proliferation or survival in hundreds of cell lines. Despite this, for specific disease subtypes, such as metastatic prostate cancer, there are likely a number of undiscovered tumor specific driver genes that may represent potential drug targets. To identify such genetic dependencies, we performed genome-scale CRISPRi screens in metastatic prostate cancer models. We then created a pipeline in which we integrated pan-cancer functional genomics data with our metastatic prostate cancer functional and clinical genomics data to identify genes that can drive aggressive prostate cancer phenotypes. Our integrative analysis of these data reveals known prostate cancer specific driver genes, such as AR and HOXB13 , as well as a number of top hits that are poorly characterized. In this study we highlight the strength of an integrated clinical and functional genomics pipeline and focus on two top hit genes, KIF4A and WDR62 . We demonstrate that both KIF4A and WDR62 drive aggressive prostate cancer phenotypes in vitro and in vivo in multiple models, irrespective of AR-status, and are also associated with poor patient outcome. It is hypothesized that there are a number of tumor specific driver genes for metastatic prostate cancer. Here, the authors perform genome-wide CRISPRi screens and integrate these data with metastatic prostate cancer functional and clinical genomics data to show that KIF4A and WDR62 drive aggressive prostate cancer phenotypes.

Autosomal dominant polycystic kidney disease (ADPKD) is caused by mutations in PKD1 and PKD2 encoding polycystin-1 (PC1) and polycystin-2 (PC2), respectively. The molecular pathways linking polycystins to cyst development in ADPKD are still unclear. Intracystic fluid secretion via ion transporters and channels plays a crucial role in cyst expansion in ADPKD. Unexpectedly, we observed significant and selective up-regulation of NHA2, a member of the SLC9B family of Na+/H+ exchangers that correlated with cyst size and disease severity in ADPKD patients. Using three-dimensional cultures of MDCK cells to model cystogenesis in vitro, we show that ectopic expression of NHA2 is causal to increased cyst size. Induction of PC1 in MDCK cells inhibited NHA2 expression with concordant inhibition of Ca2+ influx through store-dependent and independent pathways, whereas reciprocal activation of Ca2+ influx by a dominant negative, membrane-anchored C-terminal tail fragment of PC1 elevated NHA2. We show that NHA2 is a target of Ca2+/NFAT signaling and is transcriptionally induced by methylxanthine drugs such as caffeine and theophylline, which are contraindicated in ADPKD patients. Finally, we observe robust induction of NHA2 by vasopressin, which is physiologically consistent with increased levels of circulating vasopressin and up-regulation of vasopressin V2 receptors in ADPKD. Our findings have mechanistic implications on the emerging use of vasopressin V2 receptor antagonists such as tolvaptan as safe and effective therapy for PKD and reveal a potential new regulator of transepithelial salt and water transport in the kidney.

Although the mainstay of treatment for hormone responsive breast tumors is targeted endocrine therapy, many patients develop de novo or acquired resistance and are treated with chemotherapeutic drugs. The vast majority (80%) of estrogen receptor positive tumors also express wild type p53 protein that is a major determinant of the DNA damage response. Tumors that are ER+ and p53WT respond poorly to chemotherapy, although the underlying mechanisms are not completely understood. We describe a novel link between store independent Ca2+ entry (SICE) and resistance to DNA damaging drugs, mediated by the secretory pathway Ca2+-ATPase, SPCA2. In luminal ER+/PR+ breast cancer subtypes, SPCA2 levels are high and correlate with poor survival prognosis. Independent of ion pump activity, SPCA2 elevates baseline Ca2+ levels through SICE and drives cell proliferation. Attenuation of SPCA2 or depletion of extracellular Ca2+ increased mitochondrial ROS production, DNA damage and activation of the ATM/ATR-p53 axis leading to G0/G1 phase cell cycle arrest and apoptosis. Consistent with these findings, SPCA2 knockdown confers chemosensitivity to DNA damaging agents including doxorubicin, cisplatin and ionizing radiation. We conclude that elevated SPCA2 expression in ER+ p53WT breast tumors drives pro-survival and chemotherapy resistance by suppressing the DNA damage response. Drugs that target store-independent Ca2+ entry pathways may have therapeutic potential in treating receptor positive breast cancer.

Progression of benign tumors to invasive, metastatic cancer is accompanied by the epithelial to mesenchymal transition (EMT), characterized by loss of the cell-adhesion protein E-cadherin. Although silencing mutations and transcriptional repression of the E-cadherin gene have been widely studied, not much is known about post-translational regulation of E-cadherin in tumors. We show that E-cadherin is tightly co-expressed with the secretory pathway Ca2+-ATPase isoform 2, SPCA2 (ATP2C2), in breast tumors. Loss of SPCA2 impairs surface expression of E-cadherin and elicits mesenchymal gene expression through disruption of cell adhesion in tumorspheres and downstream Hippo-YAP signaling. Conversely, ectopic expression of SPCA2 in triple negative breast cancer (TNBC) elevates baseline Ca2+ and YAP phosphorylation, enhances post-translational expression of E-cadherin, and suppresses mesenchymal gene expression. Thus, loss of SPCA2 phenocopies loss of E-cadherin in the Hippo signaling pathway and EMT-MET transitions, consistent with a functional role for SPCA2 in E-cadherin biogenesis. Furthermore, we show that SPCA2 suppresses invasive phenotypes, including cell migration in vitro and tumor metastasis in vivo. Based on these findings, we propose that SPCA2 functions as a key regulator of EMT and may be a potential therapeutic target for treatment of metastatic cancer. Implications: Post-translational control of E-cadherin and the Hippo pathway by calcium signaling regulates epithelial mesenchymal transition in breast cancer cells. Footnotes * The revised manuscript has been significantly re-organized and new data have been added.

Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest—namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial—ENTHUSE M1—in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0·791; Bayes factor >5) and surpassed the reference model (iAUC 0·743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3·32, 95% CI 2·39–4·62, p<0·0001; reference model: 2·56, 1·85–3·53, p<0·0001). The new model was validated further on the ENTHUSE M1 cohort with similarly high performance (iAUC 0·768). Meta-analysis across all methods confirmed previously identified predictive clinical variables and revealed aspartate aminotransferase as an important, albeit previously under-reported, prognostic biomarker. Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer. Sanofi US Services, Project Data Sphere.

Abstract Background Although validated patient-reported outcome (PRO) measurements can categorize patients with inflammatory bowel disease (IBD) into clinical remission or active disease, patients may have different definitions of remission. The purpose of this study was to compare patient-defined remission to remission based on PRO measures and physician global assessment (PGA) and to understand the clinical and demographic factors associated with disagreements. Methods We retrospectively analyzed 3257 de-identified surveys from 2004 IBD patients who consented to participate in the Crohn’s and Colitis Foundation’s IBD Qorus Learning Health System between September 2019 and February 2021. We used logistic regression models with generalized estimating equations to analyze the clinical and demographic factors (eg, age, disease duration, health confidence) associated with discordance between patient-defined remission (yes/no) and PRO-defined remission for ulcerative colitis (UC; PRO2: stool frequency, rectal bleeding) and Crohn’s disease (CD; PRO-3: average number of liquid stools, abdominal pain, well-being). Results Among patients with UC, overall concordance was 79% between patient self-report and PRO2-defined remission and 49% between patient self-report and PGA-defined remission. Among patients with CD, overall concordance was 69% between patient self-report and PRO3-defined remission and 54% between patient self-report and PGA-defined remission. Patients in PRO-defined remission were more likely to report active disease if they had IBD <5 years and low health confidence. Patients with PRO-defined active disease were more likely to report remission if they were not using prednisone and had high health confidence. Conclusion Discordance exists between how remission is defined by patients, PRO measures, and PGA. Lay Summary Discordance between patients’ self-reported remission and remission defined based on patient-reported outcomes was observed in 31% of Crohn’s disease visits and 21% of ulcerative colitis visits. Disease duration and health confidence were associated with discordance.