Acute myeloid leukemia with LRRFIP1::FGFR1 rearrangement and a complex karyotype.

We report a case of a 20-year-old man who presented with splenomegaly, hyperleukocytosis, anemia, and thrombocytopenia. A diagnosis of acute myeloid leukemia (AML) with LRRFIP1::FGFR1 rearrangement with complex karyotype was determined. Chromosome analysis showed a male karyotype: 46,XY,i(1)(q10),t(2;8)(q37;p11.2),der(5)t(1;5) (p22;q13)[17]46,XY[3]. Fluorescence in situ hybridization (FISH) analysis using the Cytocell FGFR1 break apart/amplification probe detected FGFR1 rearrangement with t(2:8) in 126/200 cells analyzed. Other FISH probes including 1p36/ 1q25 probes, del(5q) deletion probe, TLX3 break apart probe, and PDGFRB break apart probe were also utilized to confirm the other karyotypic abnormalities. Next-generation sequencing (NGS) SureSelectXT Custom DNA Target Somatic Detection detected RUNX1 gene mutation. NGS Archer FusionPlex (RNA) confirmed the LRRFIP1::FGFR1 rearrangement. This is the second reported case of AML with LRRFIP1::FGFR1 rearrangement and the first with a complex karyotype.

T-cell priming transcriptomic markers: implications of immunome heterogeneity for precision immunotherapy.

Immune checkpoint blockade is effective for only a subset of cancers. Targeting T-cell priming markers (TPMs) may enhance activity, but proper application of these agents in the clinic is challenging due to immune complexity and heterogeneity. We interrogated transcriptomics of 15 TPMs (CD137, CD27, CD28, CD80, CD86, CD40, CD40LG, GITR, ICOS, ICOSLG, OX40, OX40LG, GZMB, IFNG, and TBX21) in a pan-cancer cohort (N = 514 patients, 30 types of cancer). TPM expression was analyzed for correlation with histological type, microsatellite instability high (MSI-H), tumor mutational burden (TMB), and programmed death-ligand 1 (PD-L1) expression. Among 514 patients, the most common histological types were colorectal (27%), pancreatic (11%), and breast cancer (10%). No statistically significant association between histological type and TPM expression was seen. In contrast, expression of GZMB (granzyme B, a serine protease stored in activated T and NK cells that induces cancer cell apoptosis) and IFNG (activates cytotoxic T cells) were significantly higher in tumors with MSI-H, TMB ≥ 10 mutations/mb and PD-L1 ≥ 1%. PD-L1 ≥ 1% was also associated with significantly higher CD137, GITR, and ICOS expression. Patients' tumors were classified into "Hot", "Mixed", or "Cold" clusters based on TPM expression using hierarchical clustering. The cold cluster showed a significantly lower proportion of tumors with PD-L1 ≥ 1%. Overall, 502 patients (98%) had individually distinct patterns of TPM expression. Diverse expression patterns of TPMs independent of histological type but correlating with other immunotherapy biomarkers (PD-L1 ≥ 1%, MSI-H and TMB ≥ 10 mutations/mb) were observed. Individualized selection of patients based on TPM immunomic profiles may potentially help with immunotherapy optimization.

Evaluation of hypereosinophilia in a case of FLT3-mutant acute myeloid leukemia treated with gilteritinib.

Acute myeloid leukemias (AMLs) frequently harbor activating mutations in Fms-like tyrosine kinase 3 (FLT3). The use of FLT3 inhibitors (FLT3i) is the standard of care for treatment of newly diagnosed and relapsed patients with AML. Differentiation responses including clinical differentiation syndrome have been previously reported with FLT3i when used as single agents in relapsed disease. We present a case of hypereosinophilia in a patient on FLT3i therapy with persistent FLT3 polymerase chain reaction (PCR) positivity in peripheral blood. We sorted mature leukocytes by lineage to determine if the eosinophils were leukemia-derived. FLT3 PCR and next-generation sequencing analysis demonstrated monocytic differentiation of the FLT3-ITD leukemic clone with reactive hypereosinophilia that was derived from a preleukemic SF3B1, FLT3 wild-type clone. Our case is the first to definitively demonstrate the emergence of clonal FLT3-ITD monocytes with FLT3i and the first to demonstrate a differentiation response following decitabine, venetoclax, and gilteritinib triplet therapy.

Development and implementation of an automated and highly accurate reporting process for NGS-based clonality testing.

B and T cells undergo random recombination of the VH/DH/JH portions of the immunoglobulin loci (B cell) and T-cell receptors before becoming functional cells. When one V-J rearrangement is over-represented in a population of B or T cells indicating an origin from a single cell, this indicates a clonal process. Clonality aids in the diagnosis and monitoring of lymphoproliferative disorders and evaluation of disease recurrence. This study aimed to develop objective criteria, which can be automated, to classify B and T cell clonality results as positive (clonal), No evidence of clonality, or invalid (failed). Using clinical samples with "gold standard" clonality data obtained using PCR/CE testing, we ran NGS-based amplicon clonality assays and developed our own model for clonality reporting. To assess the performance of our model, we analyzed the NGS results across other published models. Our model for clonality calling using NGS-based technology increases the assay's sensitivity, more accurately detecting clonality. In addition, we have built a computational pipeline to use our model to objectively call clonality in an automated fashion. Collectively the results outlined below will have a direct clinical impact by expediting the review and sign-out process for concise clonality reporting.

Spatiotemporal assessment of immunogenomic heterogeneity in multiple myeloma.

Spatial heterogeneity is a common phenomenon in metastatic solid tumors and an evolving concept in multiple myeloma (MM). The interplay between malignant plasma cells (PCs) and the microenvironment has not yet been analyzed in MM. For this purpose, we performed bone marrow aspirates and imaging-guided biopsies of corresponding lesions in newly diagnosed MM (NDMM) and relapsed/refractory MM (RRMM) patients. PCs were isolated and subjected to whole-exome sequencing (WES). Non-PCs were studied with next-generation flow (NGF) and T-cell receptor sequencing (TCRseq) to analyze the connection between malignant and nonmalignant cells in the bone marrow and in lesions. Although we observed a strong overlap from WES, NGF, and TCRseq in patients with intramedullary disease, WES revealed significant spatial heterogeneity in patients with extramedullary disease. NGF showed significant immunosuppression in RRMM compared with NDMM as indicated by fewer myeloid dendritic cells, unswitched memory B cells, Th9 cells, and CD8 effector memory T cells but more natural killer and regulatory T cells. Additionally, fewer T-cell receptor (TCR) sequences were detected in RRMM compared with NDMM and healthy individuals. After induction therapy, TCR repertoire richness increased to levels of healthy individuals, and NGF showed more regulatory T cells and myeloid-derived suppressor cells, regardless of depth of response. Clinical significance of imaging-guided biopsies of lesions was demonstrated by detection of monoclonal PCs in patients without measurable residual disease (MRD) in aspirates from the iliac crest as well as identification of secondary primary malignancies in MRD- patients. Furthermore, site-specific clones with different drug susceptibilities and genetically defined high-risk features were detected by our workflow.

Evaluation of tumor microenvironment and biomarkers of immune checkpoint inhibitor response in metastatic renal cell carcinoma.

BACKGROUND: Immunotherapy combinations including ipilimumab and nivolumab are now the standard of care for untreated metastatic renal cell carcinoma (mRCC). Biomarkers of response are lacking to predict patients who will have a favorable or unfavorable response to immunotherapy. This study aimed to use the OmniSeq transcriptome-based platform to develop biomarkers of response to immunotherapy. METHODS: Two cohorts of patients were retrospectively collected. These included an investigational cohort of patients with mRCC treated with immune checkpoint inhibitor therapy from five institutions, and a subsequent validation cohort of patients with mRCC treated with combination ipilimumab and nivolumab from two institutions (Duke Cancer Institute and Cleveland Clinic Taussig Cancer Center). Tissue-based RNA sequencing was performed using the OmniSeq Immune Report Card on banked specimens to identify gene signatures and immune checkpoints associated with differential clinical outcomes. A 5-gene expression panel was developed based on the investigational cohort and was subsequently evaluated in the validation cohort. Clinical outcomes including progression-free survival (PFS) and overall survival (OS) were extracted by retrospective chart review. Objective response rate (ORR) was assessed by Response Evaluation Criteria in Solid Tumors (RECIST) V.1.1. RESULTS: The initial investigation cohort identified 86 patients with mRCC who received nivolumab (80%, 69/86), ipilimumab/nivolumab (14%, 12/86), or pembrolizumab (6%, 5/86). A gene expression score was created using the top five genes found in responders versus non-responders (FOXP3, CCR4, KLRK1, ITK, TIGIT). The ORR in patients with high gene expression (GEhigh) on the 5-gene panel was 29% (14/48), compared with low gene expression (GElow) 3% (1/38, χ2 p=0.001). The validation cohort was comprised of 62 patients who received ipilimumab/nivolumab. There was no difference between GEhigh and GElow in terms of ORR (44% vs 38.5%), PFS (HR 1.5, 95% CI 0.58 to 3.89), or OS (HR 0.96, 95% CI 0.51 to 1.83). Similarly, no differences in ORR, PFS or OS were observed when patients were stratified by tumor mutational burden (high=top 20%), PD-L1 (programmed death-ligand 1) expression by immunohistochemistry or RNA expression, or CTLA-4 (cytotoxic T-lymphocytes-associated protein 4) RNA expression. The International Metastatic RCC Database Consortium (IMDC) risk score was prognostic for OS but not PFS. CONCLUSION: A 5-gene panel that was associated with improved ORR in a predominantly nivolumab monotherapy population of patients with mRCC was not predictive for radiographic response, PFS, or OS among patients with mRCC treated with ipilimumab and nivolumab.

Deciphering spatial genomic heterogeneity at a single cell resolution in multiple myeloma.

Osteolytic lesions (OL) characterize symptomatic multiple myeloma. The mechanisms of how malignant plasma cells (PC) cause OL in one region while others show no signs of bone destruction despite subtotal infiltration remain unknown. We report on a single-cell RNA sequencing (scRNA-seq) study of PC obtained prospectively from random bone marrow aspirates (BM) and paired imaging-guided biopsies of OL. We analyze 148,630 PC from 24 different locations in 10 patients and observe vast inter- and intra-patient heterogeneity based on scRNA-seq analyses. Beyond the limited evidence for spatial heterogeneity from whole-exome sequencing, we find an additional layer of complexity by integrated analysis of anchored scRNA-seq datasets from the BM and OL. PC from OL are characterized by differentially expressed genes compared to PC from BM, including upregulation of genes associated with myeloma bone disease like DKK1, HGF and TIMP-1 as well as recurrent downregulation of JUN/FOS, DUSP1 and HBB. Assessment of PC from longitudinally collected samples reveals transcriptional changes after induction therapy. Our study contributes to the understanding of destructive myeloma bone disease.

A scalable high-throughput targeted next-generation sequencing assay for comprehensive genomic profiling of solid tumors.

Timely and accurate identification of molecular alterations in solid tumors is essential for proper management of patients with advanced cancers. This has created a need for rapid, scalable comprehensive genomic profiling (CGP) systems that detect an increasing number of therapeutically-relevant variant types and molecular signatures. In this study, we assessed the analytical performance of the TruSight Oncology 500 High-Throughput assay for detection of somatic alterations from formalin-fixed paraffin-embedded tissue specimens. In parallel, we developed supporting software and automated sample preparation systems designed to process up to 70 clinical samples in a single NovaSeq 6000TM sequencing run with a turnaround time of <7 days from specimen receipt to report. The results demonstrate that the scalable assay accurately and reproducibly detects small variants, copy number alterations, microsatellite instability (MSI) and tumor mutational burden (TMB) from 40ng DNA, and multiple gene fusions, including known and unknown partners and splice variants from 20ng RNA. 717 tumor samples and reference materials with previously known alterations in 96 cancer-related genes were sequenced to evaluate assay performance. All variant classes were reliably detected at consistent and reportable variant allele percentages with >99% overall accuracy and precision. Our results demonstrate that the high-throughput CGP assay is a reliable method for accurate detection of molecular alterations in support of precision therapeutics in oncology. The supporting systems and scalable workflow allow for efficient interpretation and prompt reporting of hundreds of patient cancer genomes per week with excellent analytical performance.

Integration of tumor inflammation, cell proliferation, and traditional biomarkers improves prediction of immunotherapy resistance and response.

BACKGROUND: Contemporary to the rapidly evolving landscape of cancer immunotherapy is the equally changing understanding of immune tumor microenvironments (TMEs) which is crucial to the success of these therapies. Their reliance on a robust host immune response necessitates clinical grade measurements of immune TMEs at diagnosis. In this study, we describe a stable tumor immunogenic profile describing immune TMEs in multiple tumor types with ability to predict clinical benefit from immune checkpoint inhibitors (ICIs). METHODS: A tumor immunogenic signature (TIGS) was derived from targeted RNA-sequencing (RNA-seq) and gene expression analysis of 1323 clinical solid tumor cases spanning 35 histologies using unsupervised analysis. TIGS correlation with ICI response and survival was assessed in a retrospective cohort of NSCLC, melanoma and RCC tumor blocks, alone and combined with TMB, PD-L1 IHC and cell proliferation biomarkers. RESULTS: Unsupervised clustering of RNA-seq profiles uncovered a 161 gene signature where T cell and B cell activation, IFNg, chemokine, cytokine and interleukin pathways are over-represented. Mean expression of these genes produced three distinct TIGS score categories: strong (n = 384/1323; 29.02%), moderate (n = 354/1323; 26.76%), and weak (n = 585/1323; 44.22%). Strong TIGS tumors presented an improved ICI response rate of 37% (30/81); with highest response rate advantage occurring in NSCLC (ORR = 36.6%; 16/44; p = 0.051). Similarly, overall survival for strong TIGS tumors trended upward (median = 25 months; p = 0.19). Integrating the TIGS score categories with neoplastic influence quantified via cell proliferation showed highly proliferative and strong TIGS tumors correlate with significantly higher ICI ORR than poorly proliferative and weak TIGS tumors [14.28%; p = 0.0006]. Importantly, we noted that strong TIGS and highly [median = not achieved; p = 0.025] or moderately [median = 16.2 months; p = 0.025] proliferative tumors had significantly better survival compared to weak TIGS, highly proliferative tumors [median = 7.03 months]. Importantly, TIGS discriminates subpopulations of potential ICI responders that were considered negative for response by TMB and PD-L1. CONCLUSIONS: TIGS is a comprehensive and informative measurement of immune TME that effectively characterizes host immune response to ICIs in multiple tumors. The results indicate that when combined with PD-L1, TMB and cell proliferation, TIGS provides greater context of both immune and neoplastic influences on the TME for implementation into clinical practice.

Immune profiling and immunotherapeutic targets in pancreatic cancer.

BACKGROUND: Immunotherapeutic approaches for pancreatic ductal adenocarcinoma (PDAC) are less successful as compared to many other tumor types. In this study, comprehensive immune profiling was performed in order to identify novel, potentially actionable targets for immunotherapy. METHODS: Formalin-fixed paraffin embedded (FFPE) specimens from 68 patients were evaluated for expression of 395 immune-related markers (RNA-seq), mutational burden by complete exon sequencing of 409 genes, PD-L1 expression by immunohistochemistry (IHC), pattern of tumor infiltrating lymphocytes (TILs) infiltration by CD8 IHC, and PD-L1/L2 copy number by fluorescent in situ hybridization (FISH). RESULTS: The seven classes of actionable genes capturing myeloid immunosuppression, metabolic immunosuppression, alternative checkpoint blockade, CTLA-4 immune checkpoint, immune infiltrate, and programmed cell death 1 (PD-1) axis immune checkpoint, discerned 5 unique clinically relevant immunosuppression expression profiles (from most to least common): (I) combined myeloid and metabolic immunosuppression [affecting 25 of 68 patients (36.8%)], (II) multiple immunosuppressive mechanisms (29.4%), (III) PD-L1 positive (20.6%), (IV) highly inflamed PD-L1 negative (10.3%); and (V) immune desert (2.9%). The Wilcoxon rank-sum test was used to compare the PDAC cohort with a comparison cohort (n=1,416 patients) for the mean expressions of the 409 genes evaluated. Multiple genes including TIM3, VISTA, CCL2, CCR2, TGFB1, CD73, and CD39 had significantly higher mean expression versus the comparison cohort, while three genes (LAG3, GITR, CD38) had significantly lower mean expression. CONCLUSIONS: This study demonstrates that a clinically relevant unique profile of immune markers can be identified in PDAC and be used as a roadmap for personalized immunotherapeutic decision-making strategies.

Proliferative potential and response to nivolumab in clear cell renal cell carcinoma patients.

Background: Biomarkers predicting immunotherapy response in metastatic renal cell cancer (mRCC) are lacking. PD-L1 immunohistochemistry is a complementary diagnostic for immune checkpoint inhibitors (ICIs) in mRCC, but has shown minimal clinical utility and is not used in routine clinical practice. Methods: Tumor specimens from 56 patients with mRCC who received nivolumab were evaluated for PD-L1, cell proliferation (targeted RNA-seq), and outcome. Results: For 56 patients treated with nivolumab as a standard of care, there were 2 complete responses and 8 partial responses for a response rate of 17.9%. Dividing cell proliferation into tertiles, derived from the mean expression of 10 proliferation-associated genes in a reference set of tumors, poorly proliferative tumors (62.5%) were more common than moderately (30.4%) or highly proliferative (8.9%) counterparts. Moderately proliferative tumors were enriched for PD-L1 positive (41.2%), compared to poorly proliferative counterparts (11.4%). Objective response for moderately proliferative (29.4%) tumors was higher than that of poorly (11.4%) proliferative counterparts, but not statistically significant (p = .11). When cell proliferation and negative PD-L1 tumor proportion scores were combined statistically significant results were achieved (p = .048), showing that patients with poorly proliferative and PD-L1 negative tumors have a very low response rate (6.5%) compared to moderately proliferative PD-L1 negative tumors (30%). Conclusions: Cell proliferation has value in predicting response to nivolumab in clear cell mRCC patients, especially when combined with PD-L1 expression. Further studies which include the addition of progression-free survival (PFS) along with sufficiently powered subgroups are required to further support these findings.

Expression of TIM3/VISTA checkpoints and the CD68 macrophage-associated marker correlates with anti-PD1/PDL1 resistance: implications of immunogram heterogeneity.

Although immunotherapies have achieved remarkable salutary effects among subgroups of advanced cancers, most patients do not respond. We comprehensively evaluated biomarkers associated with the "cancer-immunity cycle" in the pan-cancer setting in order to understand the immune landscape of metastatic malignancies as well as anti-PD-1/PD-L1 inhibitor resistance mechanisms. Interrogation of 51 markers of the cancer-immunity cycle was performed in 101 patients with diverse malignancies using a clinical-grade RNA sequencing assay. Overall, the immune phenotypes demonstrated overexpression of multiple checkpoints including VISTA (15.8% of 101 patients), PD-L2 (10.9%), TIM3 (9.9%), LAG3 (8.9%), PD-L1 (6.9%) and CTLA4 (3.0%). Additionally, aberrant expression of macrophage-associated markers (e.g. CD68 and CSF1R; 11-23%), metabolic immune escape markers (e.g. ADORA2A and IDO1; 9-16%) and T-cell priming markers (e.g. CD40, GITR, ICOS and OX40; 4-31%) were observed. Most tumors (87.1%, 88/101) expressed distinct immune portfolios, with a median of six theoretically actionable biomarkers (pharmacologically tractable by Food and Drug Administration approved agents [on- or off-label] or with agents in clinical development). Overexpression of TIM-3, VISTA and CD68 were significantly associated with shorter progression-free survival (PFS) after anti-PD-1/PD-L1-based therapies (among 39 treated patients) (all P < .01). In conclusion, cancer-immunity cycle biomarker evaluation was feasible in diverse solid tumors. High expression of alternative checkpoints TIM-3 and VISTA and of the macrophage-associated markers CD68 were associated with significantly worse PFS after anti-PD-1/PD-L1-based therapies. Most patients had distinct and complex immune expression profiles suggesting the need for customized combinations of immunotherapy.

Complete response to anti-PD-L1 antibody in a metastatic bladder cancer associated with novel MSH4 mutation and microsatellite instability.

BACKGROUND: Microsatellite instability (MSI) occurs in 3% of urothelial carcinomas as a result of germline or somatic loss of function mutation in mismatch repair (MMR) proteins.1 Although MSH4 is a member of the DNA MMR mutS family, the association of MSH4 mutation with MSI has not been described. We report a complete responder to PD-L1 blockade who had MSH4 mutated metastatic bladder cancer with mixed histology and MSI. The genomics of urothelial, plasmacytoid and squamous histology was characterized individually through microdissection. CASE PRESENTATION: An 81-year-old man was diagnosed with metastatic urothelial carcinoma 8 months after a cystectomy for muscle invasive bladder cancer. His disease was primary refractory to first-line platinum-based chemotherapy but attained complete response to second-line atezolizumab. PCR-based assay revealed MSI high. The tumor mutational burden was elevated to 36.7 mut/Mb. However, immunohistochemistry of MLH1, MSH2, MSH6 and PMS2 was intact. Whole exome sequencing confirmed that the above mentioned four classic MMR genes were wild type but revealed a deleterious MSH4 L359I mutation with variant allele fraction of 30% and Polyphen2 score of 0.873. The association of MSH4 alterations and MSI-H was independently verified in two publicly available MSI-H colorectal cancer datasets. CONCLUSIONS: The novel MSH4 L359I mutation is associated with MSI and high mutational burden leading to remarkable response to PD-L1 blockade. More studies are warranted to establish the causality relationship between MSH4 and MSI.

Development and analytical validation of a next-generation sequencing based microsatellite instability (MSI) assay.

BACKGROUND: We have developed and analytically validated a next-generation sequencing (NGS) assay to classify microsatellite instability (MSI) in formalin-fixed paraffin-embedded (FFPE) tumor specimens. METHODOLOGY: The assay relies on DNA-seq evaluation of insertion/deletion (indel) variability at 29 highly informative genomic loci to estimate MSI status without the requirement for matched-normal tissue. The assay has a clinically relevant five-day turnaround time and can be conducted on as little as 20 ng genomic DNA with a batch size of up to forty samples in a single run. RESULTS: The MSI detection method was developed on a training set (n = 94) consisting of 22 MSI-H, 24 MSS, and 47 matched normal samples and tested on an independent test set of 24 MSI-H and 24 MSS specimens. Assay performance with respect to accuracy, reproducibility, precision as well as control sample performance was estimated across a wide range of FFPE samples of multiple histologies to address pre-analytical variability (percent tumor nuclei), and analytical variability (batch size, run, day, operator). Analytical precision studies demonstrated that the assay is highly reproducible and accurate as compared to established gold standard PCR methodology and has been validated through NYS CLEP. SIGNIFICANCE: This assay provides clinicians with robust and reproducible NGS-based MSI testing without the need of matched normal tissue to inform clinical decision making for patients with solid tumors.

Oncologist uptake of comprehensive genomic profile guided targeted therapy.

We describe the extent to which comprehensive genomic profiling (CGP) results were used by oncologists to guide targeted therapy selection in a cohort of solid tumor patients tested as part of standard care at Roswell Park Comprehensive Cancer Center June 2016-June 2017, with adequate follow up through September 2018 (n = 620). Overall, 28.4% of CGP tests advised physicians about targeted therapy use supported by companion diagnostic or practice guideline evidence. Post-test targeted therapy uptake was highest for patients in active treatment at the time of order (86% versus 76% of treatment naïve patients), but also took longer to initiate (median 50 days versus 7 days for treatment naïve patients), with few patients (2.6%) receiving targeted agents prior to testing. 100% of patients with resistance variants did not receive targeted agents. Treatment naïve patients received immunotherapy as the most common alternative. When targeted therapy given off-label or in a trial was the best CGP option, (7%) of patients received it. Our data illustrate the appropriate and heterogeneous use of CGP by oncologists as a longitudinal treatment decision tool based on patient history and treatment needs, and that some patients may benefit from testing prior to initiation of other standard treatments.

Body Mass Index Influences the Salutary Effects of Metformin on Survival After Lobectomy for Stage I NSCLC.

INTRODUCTION: Metformin, a common medication used in the treatment of diabetes mellitus is known to have anticancer effects. We hypothesized that the salutary effect of metformin on the survival of patients with stage I NSCLC is influenced by body mass index (BMI). METHODS: Patients undergoing lobectomy for stage I NSCLC without neoadjuvant therapy were included. Univariate and multivariate survival analyses to examine the association between metformin use and overall survival (OS), disease-specific survival (DSS), and recurrence-free survival were performed, stratified by BMI (>25 kg/m2 and ≤25 kg/m2). Expression of immune checkpoints in patients on metformin and not was performed in a separate cohort of 205 patients with advanced disease. RESULTS: Four hundred thirty-four stage I patients (including 74 metformin users) were deemed eligible for analysis. Univariate and multivariate analysis revealed an association between metformin use and OS (hazard ratio [HR] = 0.52; p = 0.04) as well as DSS (HR = 0.21; p = 0.04) but not recurrence-free survival (HR = 0.67; p = 0.33) in high-BMI patients only. In a separate cohort of 205 patients with tumors of all stages (including 35 metformin users), downregulation of immune checkpoint gene expression (programmed cell death 1, cytotoxic T-lymphocyte associated protein 4, B and T lymphocyte associated, CD27 molecule, lymphocyte activating 3, and inducible T cell costimulator) in metformin users was seen only in high-BMI patients, with upregulation of these genes seen in low-BMI patients with metformin use. CONCLUSIONS: Metformin use may be associated with better OS and DSS only in high-BMI patients. This hypothesis is supported by gene expression data of immune checkpoint genes in metformin users using a separate cohort of advanced-stage tumors. Further studies examining the interaction of BMI with metformin in NSCLC are worthwhile.

Accurate Quantification of Residual Cancer Cells in Pelvic Washing Reveals Association with Cancer Recurrence Following Robot-Assisted Radical Cystectomy.

PURPOSE: Bladder cancer recurrence following cystectomy remains a significant cause of bladder cancer specific mortality. Residual cancer cells contribute to cancer recurrence due to tumor spillage or undetectable preexisting micrometastatic tumor clones. We detected and quantified residual cancer cells in pelvic washing using ultradeep targeted sequencing. We compared the levels of residual cancer cells with clinical variables and cancer recurrence. MATERIALS AND METHODS: The primary tumor specimen was available in 17 patients who underwent robot-assisted radical cystectomy. All tumors had negative surgical margins. Pelvic washes and blood were collected intraoperatively before and after robot-assisted radical cystectomy, after pelvic lymph node dissection and in the suction fluid collected during the procedure. Two-step sequencing, including whole exome sequencing followed by ultradeep targeted sequencing (× greater than 50,000), was done to quantify residual cancer cells in each sample. Eight patients were excluded from study due to sample quality issues. The final analysis cohort comprised 9 patients. The residual cancer cell level was quantified for each sample as the relative cancer cell fraction and compared between time points. The peak relative cancer cell fraction of each patient was correlated with clinical and pathological variables. RESULTS: Residual cancer cells were detected in approximately half of the pelvic washing specimens during or after but not before robot-assisted radical cystectomy. Higher residual cancer cell levels were associated with aggressive variant histology and cancer recurrence. Verifying the feasibility of using residual cancer cells as a novel biomarker for recurrence requires larger cohorts. CONCLUSIONS: Detection of residual cancer cells in intraoperative peritoneal washes of patients with bladder cancer who undergo radical cystectomy may represent a robust biomarker of tumor aggressiveness and metastatic potential.

Proliferative potential and resistance to immune checkpoint blockade in lung cancer patients.

BACKGROUND: Resistance to immune checkpoint inhibitors (ICIs) has been linked to local immunosuppression independent of major ICI targets (e.g., PD-1). Clinical experience with response prediction based on PD-L1 expression suggests that other factors influence sensitivity to ICIs in non-small cell lung cancer (NSCLC) patients. METHODS: Tumor specimens from 120 NSCLC patients from 10 institutions were evaluated for PD-L1 expression by immunohistochemistry, and global proliferative profile by targeted RNA-seq. RESULTS: Cell proliferation, derived from the mean expression of 10 proliferation-associated genes (namely BUB1, CCNB2, CDK1, CDKN3, FOXM1, KIAA0101, MAD2L1, MELK, MKI67, and TOP2A), was identified as a marker of response to ICIs in NSCLC. Poorly, moderately, and highly proliferative tumors were somewhat equally represented in NSCLC, with tumors with the highest PD-L1 expression being more frequently moderately proliferative as compared to lesser levels of PD-L1 expression. Proliferation status had an impact on survival in patients with both PD-L1 positive and negative tumors. There was a significant survival advantage for moderately proliferative tumors compared to their combined highly/poorly counterparts (p = 0.021). Moderately proliferative PD-L1 positive tumors had a median survival of 14.6 months that was almost twice that of PD-L1 negative highly/poorly proliferative at 7.6 months (p = 0.028). Median survival in moderately proliferative PD-L1 negative tumors at 12.6 months was comparable to that of highly/poorly proliferative PD-L1 positive tumors at 11.5 months, but in both instances less than that of moderately proliferative PD-L1 positive tumors. Similar to survival, proliferation status has impact on disease control (DC) in patients with both PD-L1 positive and negative tumors. Patients with moderately versus those with poorly or highly proliferative tumors have a superior DC rate when combined with any classification schema used to score PD-L1 as a positive result (i.e., TPS ≥ 50% or ≥ 1%), and best displayed by a DC rate for moderately proliferative tumors of no less than 40% for any classification of PD-L1 as a negative result. While there is an over representation of moderately proliferative tumors as PD-L1 expression increases this does not account for the improved survival or higher disease control rates seen in PD-L1 negative tumors. CONCLUSIONS: Cell proliferation is potentially a new biomarker of response to ICIs in NSCLC and is applicable to PD-L1 negative tumors.

Treatment recommendations to cancer patients in the context of FDA guidance for next generation sequencing.

BACKGROUND: Regulatory approval of next generation sequencing (NGS) by the FDA is advancing the use of genomic-based precision medicine for the therapeutic management of cancer as standard care. Recent FDA guidance for the classification of genomic variants based on clinical evidence to aid clinicians in understanding the actionability of identified variants provided by comprehensive NGS panels has also been set forth. In this retrospective analysis, we interpreted and applied the FDA variant classification guidance to comprehensive NGS testing performed for advanced cancer patients and assessed oncologist agreement with NGS test treatment recommendations. METHODS: NGS comprehensive genomic profiling was performed in a CLIA certified lab (657 completed tests for 646 patients treated at Roswell Park Comprehensive Cancer Center) between June 2016 and June 2017. Physician treatment recommendations made within 120 days post-test were gathered from tested patients' medical records and classified as targeted therapy, precision medicine clinical trial, immunotherapy, hormonal therapy, chemotherapy/radiation, surgery, transplant, or non-therapeutic (hospice, surveillance, or palliative care). Agreement between NGS test report targeted therapy recommendations based on the FDA variant classification and physician targeted therapy treatment recommendations were evaluated. RESULTS: Excluding variants contraindicating targeted therapy (i.e., KRAS or NRAS mutations), at least one variant with FDA level 1 companion diagnostic supporting evidence as the most actionable was identified in 14% of tests, with physicians most frequently recommending targeted therapy (48%) for patients with these results. This stands in contrast to physicians recommending targeted therapy based on test results with FDA level 2 (practice guideline) or FDA level 3 (clinical trial or off label) evidence as the most actionable result (11 and 4%, respectively). CONCLUSIONS: We found an appropriate "dose-response" relationship between the strength of clinical evidence supporting biomarker-directed targeted therapy based on application of FDA guidance for NGS test variant classification, and subsequent treatment recommendations made by treating physicians. In view of recent changes at FDA, it is paramount to define regulatory grounds and medical policy coverage for NGS testing based on this guidance.

Next generation sequencing of PD-L1 for predicting response to immune checkpoint inhibitors.

BACKGROUND: PD-L1 immunohistochemistry (IHC) has been traditionally used for predicting clinical responses to immune checkpoint inhibitors (ICIs). However, there are at least 4 different assays and antibodies used for PD-L1 IHC, each developed with a different ICI. We set to test if next generation RNA sequencing (RNA-seq) is a robust method to determine PD-L1 mRNA expression levels and furthermore, efficacy of predicting response to ICIs as compared to routinely used, standardized IHC procedures. METHODS: A total of 209 cancer patients treated on-label by FDA-approved ICIs, with evaluable responses were assessed for PD-L1 expression by RNA-seq and IHC, based on tumor proportion score (TPS) and immune cell staining (ICS). A subset of serially diluted cases was evaluated for RNA-seq assay performance across a broad range of PD-L1 expression levels. RESULTS: Assessment of PD-L1 mRNA levels by RNA-seq demonstrated robust linearity across high and low expression ranges. PD-L1 mRNA levels assessed by RNA-seq and IHC (TPS and ICS) were highly correlated (p < 2e-16). Sub-analyses showed sustained correlation when IHC results were classified as high or low by clinically accepted cut-offs (p < 0.01), and results did not differ by tumor type or anti-PD-L1 antibody used. Overall, a combined positive PD-L1 result (≥1% IHC TPS and high PD-L1 expression by RNA-Seq) was associated with a 2-to-5-fold higher overall response rate (ORR) compared to a double negative result. Standard assessments of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) showed that a PD-L1 positive assessment for melanoma samples by RNA-seq had the lowest sensitivity (25%) but the highest PPV (72.7%). Among the three tumor types analyzed in this study, the only non-overlapping confidence interval for predicting response was for "RNA-seq low vs high" in melanoma. CONCLUSIONS: Measurement of PD-L1 mRNA expression by RNA-seq is comparable to PD-L1 expression by IHC both analytically and clinically in predicting ICI response. RNA-seq has the added advantages of being amenable to standardization and avoidance of interpretation bias. PD-L1 by RNA-seq needs to be validated in future prospective ICI clinical studies across multiple histologies.