Tracking tumour evolution in glioma through liquid biopsies of cerebrospinal fluid.

Diffuse gliomas are the most common malignant brain tumours in adults and include glioblastomas and World Health Organization (WHO) grade II and grade III tumours (sometimes referred to as lower-grade gliomas). Genetic tumour profiling is used to classify disease and guide therapy1,2, but involves brain surgery for tissue collection; repeated tumour biopsies may be necessary for accurate genotyping over the course of the disease3-10. While the detection of circulating tumour DNA (ctDNA) in the blood of patients with primary brain tumours remains challenging11,12, sequencing of ctDNA from the cerebrospinal fluid (CSF) may provide an alternative way to genotype gliomas with lower morbidity and cost13,14. We therefore evaluated the representation of the glioma genome in CSF from 85 patients with gliomas who underwent a lumbar puncture because they showed neurological signs or symptoms. Here we show that tumour-derived DNA was detected in CSF from 42 out of 85 patients (49.4%) and was associated with disease burden and adverse outcome. The genomic landscape of glioma in the CSF included a broad spectrum of genetic alterations and closely resembled the genomes of tumour biopsies. Alterations that occur early during tumorigenesis, such as co-deletion of chromosome arms 1p and 19q (1p/19q codeletion) and mutations in the metabolic genes isocitrate dehydrogenase 1 (IDH1) or IDH21,2, were shared in all matched ctDNA-positive CSF-tumour pairs, whereas growth factor receptor signalling pathways showed considerable evolution. The ability to monitor the evolution of the glioma genome through a minimally invasive technique could advance the clinical development and use of genotype-directed therapies for glioma, one of the most aggressive human cancers.

The evolution of RET inhibitor resistance in RET-driven lung and thyroid cancers.

The efficacy of the highly selective RET inhibitor selpercatinib is now established in RET-driven cancers, and we sought to characterize the molecular determinants of response and resistance. We find that the pre-treatment genomic landscape does not shape the variability of treatment response except for rare instances of RAS-mediated primary resistance. By contrast, acquired selpercatinib resistance is driven by MAPK pathway reactivation by one of two distinct routes. In some patients, on- and off-target pathway reactivation via secondary RET solvent front mutations or MET amplifications are evident. In other patients, rare RET-wildtype tumor cell populations driven by an alternative mitogenic driver are selected for by treatment. Multiple distinct mechanisms are often observed in the same patient, suggesting polyclonal resistance may be common. Consequently, sequential RET-directed therapy may require combination treatment with inhibitors targeting alternative MAPK effectors, emphasizing the need for prospective characterization of selpercatinib-treated tumors at the time of monotherapy progression.

Ribociclib and everolimus in well-differentiated foregut neuroendocrine tumors.

The mammalian target of rapamycin inhibitor everolimus is an established therapy for well-differentiated (WD) foregut neuroendocrine tumors (NETs). Pre-clinical data demonstrates a potential synergistic role for cyclin dependent kinase 4/6 inhibition and everolimus to treat this disease. In this phase II multicenter study, patients with advanced foregut WDNETs received combination ribociclib and everolimus until confirmed disease progression or unacceptable toxicity. The first 12 patients received ribociclib 300 mg three weeks in a row with a 1 week break and everolimus 2.5 mg daily (recommended phase II dose). Due to unexpected hematologic and infectious toxicities, the trial was put on hold, modified, and an additional 9 patients received ribociclib 200 mg and everolimus 2.5 mg daily. The primary end point was progression-free survival. Archived pre-treatment tumor was profiled by next-generation sequencing to evaluate for genomic markers of drug response. Twenty-one patients were treated (median age, 56; range, 24 to 77). The study did not meet the pre-specified criteria to advance to stage two. No patients experienced an objective response. Thirteen patients (62%) experienced stable disease. Median progression-free survival was 7.7 months (95% CI, 2.8 months to not reached). Eleven of the first 12 patients (92%) developed grade 2 or more myelosuppression. Ten patients (84%) experienced treatment interruption and 8 patients (67%) required dose reduction. Genetic testing in archival tumor tissue samples failed to identify a predictive biomarker of disease stabilization. The combination of ribociclib and everolimus had insufficient activity to warrant further investigation in foregut WDNETs.

PD-1 Blockade in Advanced Adrenocortical Carcinoma.

PURPOSE: Adrenocortical carcinomas (ACC) are rare and aggressive malignancies with limited treatment options. This study was undertaken to evaluate the immunogenicity of ACC. PATIENTS AND METHODS: Patients with advanced ACC were enrolled in a phase II study to evaluate the clinical activity of pembrolizumab 200 mg every 3 weeks, without restriction on prior therapy. The primary end point was objective response rate. Efficacy was correlated with tumor programmed death-ligand 1 expression, microsatellite-high and/or mismatch repair deficient (MSI-H/MMR-D) status, and somatic and germline genomic correlates. RESULTS: We enrolled 39 patients with advanced ACC and herein report after a median follow-up of 17.8 months (range, 5.4 months to 34.7 months). The objective response rate to pembrolizumab was 23% (nine patients; 95% CI, 11% to 39%), and the disease control rate was 52% (16 patients; 95% CI, 33% to 69%). The median duration of response was not reached (lower 95% CI, 4.1 months). Two of six patients with MSI-H/MMR-D tumors responded. The other seven patients with objective responses had microsatellite stable tumors. The median progression-free survival was 2.1 months (95% CI, 2.0 months to 10.7 months), and the median overall survival was 24.9 months (95% CI, 4.2 months to not reached). Thirteen percent of patients (n = 5) had treatment-related grade 3 or 4 adverse events. Tumor programmed death-ligand 1 expression and MSI-H/MMR-D status were not associated with objective response. CONCLUSION: MSI-H/MMR-D tumors, for which pembrolizumab is a standard therapy, are more common in ACC than has been recognized. In advanced ACC that is microsatellite stable, pembrolizumab provided clinically meaningful and durable antitumor activity with a manageable safety profile.

Development of Genome-Derived Tumor Type Prediction to Inform Clinical Cancer Care.

IMPORTANCE: Diagnosing the site of origin for cancer is a pillar of disease classification that has directed clinical care for more than a century. Even in an era of precision oncologic practice, in which treatment is increasingly informed by the presence or absence of mutant genes responsible for cancer growth and progression, tumor origin remains a critical factor in tumor biologic characteristics and therapeutic sensitivity. OBJECTIVE: To evaluate whether data derived from routine clinical DNA sequencing of tumors could complement conventional approaches to enable improved diagnostic accuracy. DESIGN, SETTING, AND PARTICIPANTS: A machine learning approach was developed to predict tumor type from targeted panel DNA sequence data obtained at the point of care, incorporating both discrete molecular alterations and inferred features such as mutational signatures. This algorithm was trained on 7791 tumors representing 22 cancer types selected from a prospectively sequenced cohort of patients with advanced cancer. RESULTS: The correct tumor type was predicted for 5748 of the 7791 patients (73.8%) in the training set as well as 8623 of 11 644 patients (74.1%) in an independent cohort. Predictions were assigned probabilities that reflected empirical accuracy, with 3388 cases (43.5%) representing high-confidence predictions (>95% probability). Informative molecular features and feature categories varied widely by tumor type. Genomic analysis of plasma cell-free DNA yielded accurate predictions in 45 of 60 cases (75.0%), suggesting that this approach may be applied in diverse clinical settings including as an adjunct to cancer screening. Likely tissues of origin were predicted from targeted tumor sequencing in 95 of 141 patients (67.4%) with cancers of unknown primary site. Applying this method prospectively to patients under active care enabled genome-directed reassessment of diagnosis in 2 patients initially presumed to have metastatic breast cancer, leading to the selection of more appropriate treatments, which elicited clinical responses. CONCLUSIONS AND RELEVANCE: These results suggest that the application of artificial intelligence to predict tissue of origin in oncologic practice can act as a useful complement to conventional histologic review to provide integrated pathologic diagnoses, often with important therapeutic implications.

Immuno-genomic landscape of osteosarcoma.

Limited clinical activity has been seen in osteosarcoma (OS) patients treated with immune checkpoint inhibitors (ICI). To gain insights into the immunogenic potential of these tumors, we conducted whole genome, RNA, and T-cell receptor sequencing, immunohistochemistry and reverse phase protein array profiling (RPPA) on OS specimens from 48 pediatric and adult patients with primary, relapsed, and metastatic OS. Median immune infiltrate level was lower than in other tumor types where ICI are effective, with concomitant low T-cell receptor clonalities. Neoantigen expression in OS was lacking and significantly associated with high levels of nonsense-mediated decay (NMD). Samples with low immune infiltrate had higher number of deleted genes while those with high immune infiltrate expressed higher levels of adaptive resistance pathways. PARP2 expression levels were significantly negatively associated with the immune infiltrate. Together, these data reveal multiple immunosuppressive features of OS and suggest immunotherapeutic opportunities in OS patients.

A rectal cancer organoid platform to study individual responses to chemoradiation.

Rectal cancer (RC) is a challenging disease to treat that requires chemotherapy, radiation and surgery to optimize outcomes for individual patients. No accurate model of RC exists to answer fundamental research questions relevant to patients. We established a biorepository of 65 patient-derived RC organoid cultures (tumoroids) from patients with primary, metastatic or recurrent disease. RC tumoroids retained molecular features of the tumors from which they were derived, and their ex vivo responses to clinically relevant chemotherapy and radiation treatment correlated with the clinical responses noted in individual patients' tumors. Upon engraftment into murine rectal mucosa, human RC tumoroids gave rise to invasive RC followed by metastasis to lung and liver. Importantly, engrafted tumors displayed the heterogenous sensitivity to chemotherapy observed clinically. Thus, the biology and drug sensitivity of RC clinical isolates can be efficiently interrogated using an organoid-based, ex vivo platform coupled with in vivo endoluminal propagation in animals.

Interactive calculator for operating characteristics of phase I cancer clinical trials using standard 3+3 designs.

Among various Phase I clinical trial designs, rule-based standard 3 + 3 designs are the most widely utilized for their simplicity and robustness. It is necessary to define crucial operating characteristics of a Phase I clinical trial before it starts. Based on the assumed probability of dose limiting toxicity (DLT) at each tested dose level, Lin and Shih elaborated formulas to calculate the five key operating characteristics of Phase I clinical trials using the two subtypes of standard 3 + 3 designs (with vs without dose de-escalation): probability of each dose level being chosen as the maximum tolerated dose (MTD); expected number of patients treated at each dose level; expected number of patients experiencing DLT at each dose level; target toxicity level (TTL) (expected probability of DLT at MTD); expected total number of patients experiencing DLT. Understanding these formulas requires advanced statistical knowledge and the formulas are too complicated to be used directly. To facilitate their application, we have developed stand-alone interactive software for convenient calculation of these key operating characteristics. The calculated results are presented in tables and plots that can be saved and easily edited for further use. Some examples of calculation using the software are presented and discussed.

High-dimensional regression analysis links magnetic resonance imaging features and protein expression and signaling pathway alterations in breast invasive carcinoma.

BACKGROUND: Imaging features derived from MRI scans can be used for not only breast cancer detection and measuring disease extent, but can also determine gene expression and patient outcomes. The relationships between imaging features, gene/protein expression, and response to therapy hold potential to guide personalized medicine. We aim to characterize the relationship between radiologist-annotated tumor phenotypic features (based on MRI) and the underlying biological processes (based on proteomic profiling) in the tumor. METHODS: Multiple-response regression of the image-derived, radiologist-scored features with reverse-phase protein array expression levels generated association coefficients for each combination of image-feature and protein in the RPPA dataset. Significantly-associated proteins for features were analyzed with Ingenuity Pathway Analysis software. Hierarchical clustering of the results of the pathway analysis determined which features were most strongly correlated with pathway activity and cellular functions. RESULTS: Each of the twenty-nine imaging features was found to have a set of significantly correlated molecules, associated biological functions, and pathways. CONCLUSIONS: We interrogated the pathway alterations represented by the protein expression associated with each imaging feature. Our study demonstrates the relationships between biological processes (via proteomic measurements) and MRI features within breast tumors.