Generalizability of a Machine Learning Model for Improving Utilization of Parathyroid Hormone-Related Peptide Testing across Multiple Clinical Centers.

BACKGROUND: Measuring parathyroid hormone-related peptide (PTHrP) helps diagnose the humoral hypercalcemia of malignancy, but is often ordered for patients with low pretest probability, resulting in poor test utilization. Manual review of results to identify inappropriate PTHrP orders is a cumbersome process. METHODS: Using a dataset of 1330 patients from a single institute, we developed a machine learning (ML) model to predict abnormal PTHrP results. We then evaluated the performance of the model on two external datasets. Different strategies (model transporting, retraining, rebuilding, and fine-tuning) were investigated to improve model generalizability. Maximum mean discrepancy (MMD) was adopted to quantify the shift of data distributions across different datasets. RESULTS: The model achieved an area under the receiver operating characteristic curve (AUROC) of 0.936, and a specificity of 0.842 at 0.900 sensitivity in the development cohort. Directly transporting this model to two external datasets resulted in a deterioration of AUROC to 0.838 and 0.737, with the latter having a larger MMD corresponding to a greater data shift compared to the original dataset. Model rebuilding using site-specific data improved AUROC to 0.891 and 0.837 on the two sites, respectively. When external data is insufficient for retraining, a fine-tuning strategy also improved model utility. CONCLUSIONS: ML offers promise to improve PTHrP test utilization while relieving the burden of manual review. Transporting a ready-made model to external datasets may lead to performance deterioration due to data distribution shift. Model retraining or rebuilding could improve generalizability when there are enough data, and model fine-tuning may be favorable when site-specific data is limited.

Genetic characterization of primary and metastatic high-grade serous ovarian cancer tumors reveals distinct features associated with survival.

High-grade serous ovarian cancer (HGSC) is the most lethal histotype of ovarian cancer and the majority of cases present with metastasis and late-stage disease. Over the last few decades, the overall survival for patients has not significantly improved, and there are limited targeted treatment options. We aimed to better characterize the distinctions between primary and metastatic tumors based on short- or long-term survival. We characterized 39 matched primary and metastatic tumors by whole exome and RNA sequencing. Of these, 23 were short-term (ST) survivors (overall survival (OS) < 3.5 years) and 16 were long-term (LT) survivors (OS > 5 years). We compared somatic mutations, copy number alterations, mutational burden, differential gene expression, immune cell infiltration, and gene fusion predictions between the primary and metastatic tumors and between ST and LT survivor cohorts. There were few differences in RNA expression between paired primary and metastatic tumors, but significant differences between the transcriptomes of LT and ST survivors in both their primary and metastatic tumors. These findings will improve the understanding of the genetic variation in HGSC that exist between patients with different prognoses and better inform treatments by identifying new targets for drug development.

Distinct clonal identities of B-ALLs arising after lenolidomide therapy for multiple myeloma.

Patients with multiple myeloma (MM) who are treated with lenalidomide rarely develop a secondary B-cell acute lymphoblastic leukemia (B-ALL). The clonal and biological relationship between these sequential malignancies is not yet clear. We identified 17 patients with MM treated with lenalidomide, who subsequently developed B-ALL. Patient samples were evaluated through sequencing, cytogenetics/fluorescence in situ hybridization (FISH), immunohistochemical (IHC) staining, and immunoglobulin heavy chain (IgH) clonality assessment. Samples were assessed for shared mutations and recurrently mutated genes. Through whole exome sequencing and cytogenetics/FISH analysis of 7 paired samples (MM vs matched B-ALL), no mutational overlap between samples was observed. Unique dominant IgH clonotypes between the tumors were observed in 5 paired MM/B-ALL samples. Across all 17 B-ALL samples, 14 (83%) had a TP53 variant detected. Three MM samples with sufficient sequencing depth (>500×) revealed rare cells (average of 0.6% variant allele frequency, or 1.2% of cells) with the same TP53 variant identified in the subsequent B-ALL sample. A lack of mutational overlap between MM and B-ALL samples shows that B-ALL developed as a second malignancy arising from a founding population of cells that likely represented unrelated clonal hematopoiesis caused by a TP53 mutation. The recurrent variants in TP53 in the B-ALL samples suggest a common path for malignant transformation that may be similar to that of TP53-mutant, treatment-related acute myeloid leukemia. The presence of rare cells containing TP53 variants in bone marrow at the initiation of lenalidomide treatment suggests that cellular populations containing TP53 variants expand in the presence of lenalidomide to increase the likelihood of B-ALL development.

CIViCdb 2022: evolution of an open-access cancer variant interpretation knowledgebase.

CIViC (Clinical Interpretation of Variants in Cancer; civicdb.org) is a crowd-sourced, public domain knowledgebase composed of literature-derived evidence characterizing the clinical utility of cancer variants. As clinical sequencing becomes more prevalent in cancer management, the need for cancer variant interpretation has grown beyond the capability of any single institution. CIViC contains peer-reviewed, published literature curated and expertly-moderated into structured data units (Evidence Items) that can be accessed globally and in real time, reducing barriers to clinical variant knowledge sharing. We have extended CIViC's functionality to support emergent variant interpretation guidelines, increase interoperability with other variant resources, and promote widespread dissemination of structured curated data. To support the full breadth of variant interpretation from basic to translational, including integration of somatic and germline variant knowledge and inference of drug response, we have enabled curation of three new Evidence Types (Predisposing, Oncogenic and Functional). The growing CIViC knowledgebase has over 300 contributors and distributes clinically-relevant cancer variant data currently representing >3200 variants in >470 genes from >3100 publications.

Neoadjuvant and Adjuvant Pembrolizumab in Resectable Locally Advanced, Human Papillomavirus-Unrelated Head and Neck Cancer: A Multicenter, Phase II Trial.

PURPOSE: Pembrolizumab improved survival in patients with recurrent or metastatic head and neck squamous-cell carcinoma (HNSCC). The aims of this study were to determine if pembrolizumab would be safe, result in pathologic tumor response (pTR), and lower the relapse rate in patients with resectable human papillomavirus (HPV)-unrelated HNSCC. PATIENTS AND METHODS: Neoadjuvant pembrolizumab (200 mg) was administered and followed 2 to 3 weeks later by surgical tumor ablation. Postoperative (chemo)radiation was planned. Patients with high-risk pathology (positive margins and/or extranodal extension) received adjuvant pembrolizumab. pTR was quantified as the proportion of the resection bed with tumor necrosis, keratinous debris, and giant cells/histiocytes: pTR-0 (<10%), pTR-1 (10%-49%), and pTR-2 (≥50%). Coprimary endpoints were pTR-2 among all patients and 1-year relapse rate in patients with high-risk pathology (historical: 35%). Correlations of baseline PD-L1 and T-cell infiltration with pTR were assessed. Tumor clonal dynamics were evaluated (ClinicalTrials.gov NCT02296684). RESULTS: Thirty-six patients enrolled. After neoadjuvant pembrolizumab, serious (grades 3-4) adverse events and unexpected surgical delays/complications did not occur. pTR-2 occurred in eight patients (22%), and pTR-1 in eight other patients (22%). One-year relapse rate among 18 patients with high-risk pathology was 16.7% (95% confidence interval, 3.6%-41.4%). pTR ≥10% correlated with baseline tumor PD-L1, immune infiltrate, and IFNγ activity. Matched samples showed upregulation of inhibitory checkpoints in patients with pTR-0 and confirmed clonal loss in some patients. CONCLUSIONS: Among patients with locally advanced, HPV-unrelated HNSCC, pembrolizumab was safe, and any pathologic response was observed in 44% of patients with 0% pathologic complete responses. The 1-year relapse rate in patients with high-risk pathology was lower than historical.

Standard operating procedure for curation and clinical interpretation of variants in cancer.

Manually curated variant knowledgebases and their associated knowledge models are serving an increasingly important role in distributing and interpreting variants in cancer. These knowledgebases vary in their level of public accessibility, and the complexity of the models used to capture clinical knowledge. CIViC (Clinical Interpretation of Variants in Cancer - www.civicdb.org) is a fully open, free-to-use cancer variant interpretation knowledgebase that incorporates highly detailed curation of evidence obtained from peer-reviewed publications and meeting abstracts, and currently holds over 6300 Evidence Items for over 2300 variants derived from over 400 genes. CIViC has seen increased adoption by, and also undertaken collaboration with, a wide range of users and organizations involved in research. To enhance CIViC's clinical value, regular submission to the ClinVar database and pursuit of other regulatory approvals is necessary. For this reason, a formal peer reviewed curation guideline and discussion of the underlying principles of curation is needed. We present here the CIViC knowledge model, standard operating procedures (SOP) for variant curation, and detailed examples to support community-driven curation of cancer variants.

Open-Sourced CIViC Annotation Pipeline to Identify and Annotate Clinically Relevant Variants Using Single-Molecule Molecular Inversion Probes.

PURPOSE: Clinical targeted sequencing panels are important for identifying actionable variants for patients with cancer; however, existing approaches do not provide transparent and rationally designed clinical panels to accommodate the rapidly growing knowledge within oncology. MATERIALS AND METHODS: We used the Clinical Interpretations of Variants in Cancer (CIViC) database to develop an Open-Sourced CIViC Annotation Pipeline (OpenCAP). OpenCAP provides methods to identify variants within the CIViC database, build probes for variant capture, use probes on prospective samples, and link somatic variants to CIViC clinical relevance statements. OpenCAP was tested using a single-molecule molecular inversion probe (smMIP) capture design on 27 cancer samples from 5 tumor types. In total, 2,027 smMIPs were designed to target 111 eligible CIViC variants (61.5 kb of genomic space). RESULTS: When compared with orthogonal sequencing, CIViC smMIP sequencing demonstrated a 95% sensitivity for variant detection (n = 61 of 64 variants). Variant allele frequencies for variants identified on both sequencing platforms were highly concordant (Pearson's r = 0.885; n = 61 variants). Moreover, for individuals with paired tumor and normal samples (n = 12), 182 clinically relevant variants missed by orthogonal sequencing were discovered by CIViC smMIP sequencing. CONCLUSION: The OpenCAP design paradigm demonstrates the utility of an open-source and open-access database built on attendant community contributions with peer-reviewed interpretations. Use of a public repository for variant identification, probe development, and variant interpretation provides a transparent approach to build dynamic next-generation sequencing-based oncology panels.

Standard operating procedure for somatic variant refinement of sequencing data with paired tumor and normal samples.

PURPOSE: Following automated variant calling, manual review of aligned read sequences is required to identify a high-quality list of somatic variants. Despite widespread use in analyzing sequence data, methods to standardize manual review have not been described, resulting in high inter- and intralab variability. METHODS: This manual review standard operating procedure (SOP) consists of methods to annotate variants with four different calls and 19 tags. The calls indicate a reviewer's confidence in each variant and the tags indicate commonly observed sequencing patterns and artifacts that inform the manual review call. Four individuals were asked to classify variants prior to, and after, reading the SOP and accuracy was assessed by comparing reviewer calls with orthogonal validation sequencing. RESULTS: After reading the SOP, average accuracy in somatic variant identification increased by 16.7% (p value = 0.0298) and average interreviewer agreement increased by 12.7% (p value < 0.001). Manual review conducted after reading the SOP did not significantly increase reviewer time. CONCLUSION: This SOP supports and enhances manual somatic variant detection by improving reviewer accuracy while reducing the interreviewer variability for variant calling and annotation.

Author Correction: The prognostic effects of somatic mutations in ER-positive breast cancer.

The original version of this Article contained errors in the depiction of confidence intervals in the NF1 BCSS data illustrated in Figure 3b. These have now been corrected in both the PDF and HTML versions of the Article. The incorrect version of Figure 3b is presented in the associated Author Correction.

Recurrent WNT pathway alterations are frequent in relapsed small cell lung cancer.

Nearly all patients with small cell lung cancer (SCLC) eventually relapse with chemoresistant disease. The molecular mechanisms driving chemoresistance in SCLC remain un-characterized. Here, we describe whole-exome sequencing of paired SCLC tumor samples procured at diagnosis and relapse from 12 patients, and unpaired relapse samples from 18 additional patients. Multiple somatic copy number alterations, including gains in ABCC1 and deletions in MYCL, MSH2, and MSH6, are identifiable in relapsed samples. Relapse samples also exhibit recurrent mutations and loss of heterozygosity in regulators of WNT signaling, including CHD8 and APC. Analysis of RNA-sequencing data shows enrichment for an ASCL1-low expression subtype and WNT activation in relapse samples. Activation of WNT signaling in chemosensitive human SCLC cell lines through APC knockdown induces chemoresistance. Additionally, in vitro-derived chemoresistant cell lines demonstrate increased WNT activity. Overall, our results suggest WNT signaling activation as a mechanism of chemoresistance in relapsed SCLC.

The prognostic effects of somatic mutations in ER-positive breast cancer.

Here we report targeted sequencing of 83 genes using DNA from primary breast cancer samples from 625 postmenopausal (UBC-TAM series) and 328 premenopausal (MA12 trial) hormone receptor-positive (HR+) patients to determine interactions between somatic mutation and prognosis. Independent validation of prognostic interactions was achieved using data from the METABRIC study. Previously established associations between MAP3K1 and PIK3CA mutations with luminal A status/favorable prognosis and TP53 mutations with Luminal B/non-luminal tumors/poor prognosis were observed, validating the methodological approach. In UBC-TAM, NF1 frame-shift nonsense (FS/NS) mutations were also a poor outcome driver that was validated in METABRIC. For MA12, poor outcome associated with PIK3R1 mutation was also reproducible. DDR1 mutations were strongly associated with poor prognosis in UBC-TAM despite stringent false discovery correction (q = 0.0003). In conclusion, uncommon recurrent somatic mutations should be further explored to create a more complete explanation of the highly variable outcomes that typifies ER+ breast cancer.

DGIdb 3.0: a redesign and expansion of the drug-gene interaction database.

The drug-gene interaction database (DGIdb, www.dgidb.org) consolidates, organizes and presents drug-gene interactions and gene druggability information from papers, databases and web resources. DGIdb normalizes content from 30 disparate sources and allows for user-friendly advanced browsing, searching and filtering for ease of access through an intuitive web user interface, application programming interface (API) and public cloud-based server image. DGIdb v3.0 represents a major update of the database. Nine of the previously included 24 sources were updated. Six new resources were added, bringing the total number of sources to 30. These updates and additions of sources have cumulatively resulted in 56 309 interaction claims. This has also substantially expanded the comprehensive catalogue of druggable genes and anti-neoplastic drug-gene interactions included in the DGIdb. Along with these content updates, v3.0 has received a major overhaul of its codebase, including an updated user interface, preset interaction search filters, consolidation of interaction information into interaction groups, greatly improved search response times and upgrading the underlying web application framework. In addition, the expanded API features new endpoints which allow users to extract more detailed information about queried drugs, genes and drug-gene interactions, including listings of PubMed IDs, interaction type and other interaction metadata.

NeoPalAna: Neoadjuvant Palbociclib, a Cyclin-Dependent Kinase 4/6 Inhibitor, and Anastrozole for Clinical Stage 2 or 3 Estrogen Receptor-Positive Breast Cancer.

Purpose: Cyclin-dependent kinase (CDK) 4/6 drives cell proliferation in estrogen receptor-positive (ER+) breast cancer. This single-arm phase II neoadjuvant trial (NeoPalAna) assessed the antiproliferative activity of the CDK4/6 inhibitor palbociclib in primary breast cancer as a prelude to adjuvant studies.Experimental Design: Eligible patients with clinical stage II/III ER+/HER2- breast cancer received anastrozole 1 mg daily for 4 weeks (cycle 0; with goserelin if premenopausal), followed by adding palbociclib (125 mg daily on days 1-21) on cycle 1 day 1 (C1D1) for four 28-day cycles unless C1D15 Ki67 > 10%, in which case patients went off study due to inadequate response. Anastrozole was continued until surgery, which occurred 3 to 5 weeks after palbociclib exposure. Later patients received additional 10 to 12 days of palbociclib (Cycle 5) immediately before surgery. Serial biopsies at baseline, C1D1, C1D15, and surgery were analyzed for Ki67, gene expression, and mutation profiles. The primary endpoint was complete cell cycle arrest (CCCA: central Ki67 ≤ 2.7%).Results: Fifty patients enrolled. The CCCA rate was significantly higher after adding palbociclib to anastrozole (C1D15 87% vs. C1D1 26%, P < 0.001). Palbociclib enhanced cell-cycle control over anastrozole monotherapy regardless of luminal subtype (A vs. B) and PIK3CA status with activity observed across a broad range of clinicopathologic and mutation profiles. Ki67 recovery at surgery following palbociclib washout was suppressed by cycle 5 palbociclib. Resistance was associated with nonluminal subtypes and persistent E2F-target gene expression.Conclusions: Palbociclib is an active antiproliferative agent for early-stage breast cancer resistant to anastrozole; however, prolonged administration may be necessary to maintain its effect. Clin Cancer Res; 23(15); 4055-65. ©2017 AACR.

Comprehensive genomic analysis reveals FLT3 activation and a therapeutic strategy for a patient with relapsed adult B-lymphoblastic leukemia.

The genomic events responsible for the pathogenesis of relapsed adult B-lymphoblastic leukemia (B-ALL) are not yet clear. We performed integrative analysis of whole-genome, whole-exome, custom capture, whole-transcriptome (RNA-seq), and locus-specific genomic assays across nine time points from a patient with primary de novo B-ALL. Comprehensive genome and transcriptome characterization revealed a dramatic tumor evolution during progression, yielding a tumor with complex clonal architecture at second relapse. We observed and validated point mutations in EP300 and NF1, a highly expressed EP300-ZNF384 gene fusion, a microdeletion in IKZF1, a focal deletion affecting SETD2, and large deletions affecting RB1, PAX5, NF1, and ETV6. Although the genome analysis revealed events of potential biological relevance, no clinically actionable treatment options were evident at the time of the second relapse. However, transcriptome analysis identified aberrant overexpression of the targetable protein kinase encoded by the FLT3 gene. Although the patient had refractory disease after salvage therapy for the second relapse, treatment with the FLT3 inhibitor sunitinib rapidly induced a near complete molecular response, permitting the patient to proceed to a matched-unrelated donor stem cell transplantation. The patient remains in complete remission more than 4 years later. Analysis of this patient's relapse genome revealed an unexpected, actionable therapeutic target that led to a specific therapy associated with a rapid clinical response. For some patients with relapsed or refractory cancers, this approach may indicate a novel therapeutic intervention that could alter outcome.

A Phase I Trial of BKM120 (Buparlisib) in Combination with Fulvestrant in Postmenopausal Women with Estrogen Receptor-Positive Metastatic Breast Cancer.

PURPOSE: This trial was conducted to determine the maximum tolerated dose (MTD) and preliminary efficacy of buparlisib, an oral pan-class I PI3K inhibitor, plus fulvestrant in postmenopausal women with metastatic estrogen receptor positive (ER(+)) breast cancer. EXPERIMENTAL DESIGN: Phase IA employed a 3+3 design to determine the MTD of buparlisib daily plus fulvestrant. Subsequent cohorts (phase IB and cohort C) evaluated intermittent (5/7-day) and continuous dosing of buparlisib (100 mg daily). No more than 3 prior systemic treatments in the metastatic setting were allowed in these subsequent cohorts. RESULTS: Thirty-one patients were enrolled. MTD was defined as buparlisib 100 mg daily plus fulvestrant. Common adverse events (AE) included fatigue (38.7%), transaminases elevation (35.5%), rash (29%), and diarrhea (19.4%). C-peptide was significantly increased during treatment, consistent with on-target effect of buparlisib. Compared with intermittent dosing, daily buparlisib was associated with more frequent early onset AEs and higher buparlisib plasma concentrations. Among the 29 evaluable patients, the clinical benefit rate was 58.6% (95% CI, 40.7%-74.5%). Response was not associated with PIK3CA mutation or treatment cohort; however, loss of PTEN, progesterone receptor (PgR) expression, or mutation in TP53 was most common in resistant cases, and mutations inAKT1 and ESR1 did not exclude treatment response. CONCLUSIONS: Buparlisib plus fulvestrant is clinically active with manageable AEs in patients with metastatic ER(+)breast cancer. Weekend breaks in buparlisib dosing reduced toxicity. Patients with PgR negative and TP53 mutation did poorly, suggesting buparlisib plus fulvestrant may not be adequately effective against tumors with these poor prognostic molecular features.

DGIdb: mining the druggable genome.

The Drug-Gene Interaction database (DGIdb) mines existing resources that generate hypotheses about how mutated genes might be targeted therapeutically or prioritized for drug development. It provides an interface for searching lists of genes against a compendium of drug-gene interactions and potentially 'druggable' genes. DGIdb can be accessed at http://dgidb.org/.