Outcomes of a Single Isocenter Brain Multi-Metastases Linear Accelerator Delivered Stereotactic Radiosurgery (SRS)

PURPOSE/OBJECTIVE(S)

The management of brain metastases has evolved from using 2D whole brain radiotherapy (WBRT) to more complex techniques like stereotactic radiosurgery (SRS) for patients with limited disease. Long-term control of lesions is challenging with WBRT techniques but treating multiple lesions with traditional SRS, where each lesion is treated on its own isocenter, can be time-consuming and difficult on patients, especially those with claustrophobia. Single Isocenter Multiple Metastases (SIMM) SRS has emerged as an option to deliver ablative SRS doses simultaneously to multiple brain metastases using a single isocenter, thereby limiting the duration of treatments for patients. Though appealing, SIMM SRS adds technical complexity and could potentially lead to worse outcomes or more complications relative to traditional SRS treatments. Given the current paucity of clinical evidence supporting SIMM SRS, we sought to retrospectively review our institution's outcomes and complications for patients treated with SIMM SRS to determine the efficacy and safety of this approach in our hands.

MATERIALS/METHODS

Patients treated at our institution with SIMM SRS with at least one post-treatment brain MRI were identified. Date on patient clinical characteristics, planning, and treatment characteristics, and outcomes were retrospectively collected. Post-treatment tumor control was evaluated with follow-up MRI imaging based on RANO criteria. Correlation between tumor control and toxicity was done by assessing radiation doses, PTV coverage, and normal brain V12 constraints.

RESULTS

A total of 27 patients received SIMM SRS from January 2015 to February 2022. The median age at first SIMM SRS was 61 (range: 38-87). The most common disease sites were lung (63.0%), breast (18.5%), and GI (7.4%). The 27 patients had 47 SIMM SRS treatments of 163 lesions total. The median number of lesions treated per isocenter was 3 (range: 2-9). 5 patients had 2 SIMM SRS isocenters treated on the same day, treating clusters of lesions (ranging from 5-11 lesions treated on that day). The most common locations involved were frontal, cerebellar, and parietal lobes (32.52%, 21.47%, and 15.34%). The modal dose was 22 Gy (range: 18-24 Gy). Median OS from initial primary diagnosis was 23.23 months, and 9.92 months after the first SIMM SRS treatment. The median imaging follow-up was 9.8 months per lesion, and the local control rate was 95.03%. 2 lesions (1.23%) developed radiation necrosis and the median time to RT necrosis among those lesions was 5.7 months after treatment.

CONCLUSION

The utilization of SIMM SRS demonstrates acceptable efficacy and safety as it has been implemented at our institution. Further studies to evaluate this planning modality are warranted to establish suitable candidates for SIMM SRS as well as evaluate the long-term outcomes for these patients.

T-cell receptor beta variable gene polymorphism predicts immune-related adverse events during checkpoint blockade immunotherapy

BACKGROUND

Immune checkpoint inhibitors have revolutionized cancer treatment. However, they are associated with a unique spectrum of side effects, called immune-related adverse events (irAEs), which can cause significant morbidity and quickly progress to severe or life-threatening events if not treated promptly. Identifying predictive biomarkers for irAEs before immunotherapy initiation is therefore a critical area of research. Polymorphisms within the T-cell receptor beta (TCRB) variable (TRBV) gene have been implicated in autoimmune disease and may be mechanistically linked to irAEs. However, the repetitive nature of the TCRB locus and incomplete genome assembly has hampered the evaluation of TRBV polymorphisms in the past.

PATIENTS AND METHODS

We used a novel method for long-amplicon next generation sequencing of rearranged TCRB chains from peripheral blood total RNA to evaluate the link between TRBV polymorphisms and irAEs in patients treated with immunotherapy for cancer. We employed multiplex PCR to create amplicons spanning the three beta chain complementarity-determining regions (CDR) regions to enable detection of polymorphism within the germline-encoded framework and CDR1 and CDR2 regions in addition to CDR3 profiling. Resultant amplicons were sequenced via the Ion Torrent and TRBV allele profiles constructed for each individual was correlated with irAE annotations to identify haplotypes associated with severe irAEs (≥ grade 3).

RESULTS

Our study included 81 patients who had irAEs when treated with immunotherapy for cancer. By using principal component analysis of the 81 TRBV allele profiles followed by k-means clustering, we identified six major TRBV haplotypes. Strikingly, we found that one-third of this cohort possessed a TRBV allele haplotype that appeared to be protective against severe irAEs.

CONCLUSION

The data suggest that long-amplicon TCRB repertoire sequencing can potentially identify TRBV haplotype groups that correlate with the risk of severe irAEs. Germline-encoded TRBV polymorphisms may serve as a predictive biomarker of severe irAEs.

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.

Technology Usage and Impacts by COVID-19 among Patients in a Radiation Oncology Clinic

Purpose/Objective(s)

Mobile devices provide platforms for consistent and real time symptom tracking for cancer patients, allowing for better symptom reporting and more timely interventions. There is limited research investigating barriers to adoption within the oncology setting and COVID-19 impacts on patent willingness to use health technology. Understanding these issues is key to successful development and implementation. We designed a survey to assess patient willingness and barriers to using mobile devices to report/track symptoms (e-report).

Materials/Methods

Two cohorts of adult patients completed a 21-question anonymized survey. The survey was administered to clinic patients before (PRE) and 18mo after (POST) the start of the COVID pandemic. Three additional questions were added to POST survey to investigate impacts from COVID. Demographics, technology usage, willingness to report data, barriers to utilization, and changes due to COVID were evaluated using descriptive statistics. Predictors of willingness to e-report, barriers to use, and changes due to the COVID-19 pandemic were analyzed using univariate and multivariate logistic regression (MVA).

Results

318 patients completed the survey (PRE= 144 patients; POST= 174 patients) with mean age 65y, 75% Caucasian, 55% male. Altogether, 75% used a smart phone (PRE=66.7%; POST=81.3%; p 0.003), 90% reported home internet access (PRE=87.5%; POST=91.4%; p 0.259), 86% used a computer (PRE=79.2%; POST=90.8%; p 0.004), and 26% used a wearable health tracker (PRE 25.7%; POST 26.4%; p 0.881). On MVA, age>65 (OR 0.32; p 0.001), annual income>50K (OR 2.16; p 0.032), smart phone ownership (OR 4.07; p 0.000), and new/current patient status (OR 2.15; p 0.020) were all significant factors impacting willingness to e- report. Limited tech literacy (p 0.024) and time commitment (p 0.048) were the only significant barriers. Privacy as a barrier was greater in PRE vs POST cohort (OR 2.3 vs OR 1.1) trending toward significance. Nearly all modes of tech usage were greater in POST vs PRE cohort. POST cohort was significantly more willing to e- report (81.1% vs 69.1%; OR 1.91; p 0.016). This remained significant on MVA after adjusting for age, concern for privacy, tech literacy, and patient status (OR 1.88; p 0.026). Furthermore, 51% of POST cohort reported the pandemic directly influenced their willingness to e-report (40% more, 11% less).

Conclusion

Radiation oncology patients are willing to use mobile technology to report symptoms. Willingness increases with decreasing age, increasing annual income, smartphone ownership, and new/current patient status. Significant barriers include tech literacy and time commitment. Post-pandemic patients are more willing to e-report and list fewer barriers. The COVID-19 pandemic appears to have had a positive impact on technology usage by patients. Efforts to develop and test mobile applications for this population are justified.

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 (GE_high) on the 5-gene panel was 29% (14/48), compared with low gene expression (GE_low) 3% (1/38, χ² p=0.001). The validation cohort was comprised of 62 patients who received ipilimumab/nivolumab. There was no difference between GE_high and GE_low 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.

Multiple functions of the DEAD-box RNA helicase, DDX5 (p68), make DDX5 a superior oncogenic biomarker and target for targeted cancer therapy

DDX5 (p68) is a well-known multifunctional DEAD-box RNA helicase and a transcription cofactor. Since its initial discovery more than three decades ago, DDX5 is gradually recognized as a potential biomarker and target for the treatment of various cancer types. Studies over the years significantly expanded our understanding of the functional diversity of DDX5 in various cancer types and extended our knowledge of its Mechanism of Action (MOA). This provides a rationale for the development of novel cancer therapeutics by using DDX5 as a biomarker and a therapeutic target. However, while most of the published studies have found DDX5 to be an oncogenic target and a cancer treatment-resistant biomarker, a few studies have reported that in certain scenarios, DDX5 may act as a tumor suppressor. After careful review of all the available relevant studies in the literature, we found that the multiple functions of DDX5 make it both a superior independent oncogenic biomarker and target for targeted cancer therapy. In this article, we will summarize the relevant studies on DDX5 in literature with a careful analysis and discussion of any inconsistencies encountered, and then provide our conclusions with respect to understanding the MOA of FL118, a novel small molecule. We hope that such a review will stimulate further discussion on this topic and assist in developing better strategies to treat cancer by using DDX5 as both an oncogenic biomarker and therapeutic target.

T-cell CX3CR1 expression as a dynamic blood-based biomarker of response to immune checkpoint inhibitors

Immune checkpoint inhibitors (ICI) have revolutionized treatment for various cancers; however, durable response is limited to only a subset of patients. Discovery of blood-based biomarkers that reflect dynamic change of the tumor microenvironment, and predict response to ICI, will markedly improve current treatment regimens. Here, we investigate CX3C chemokine receptor 1 (CX3CR1), a marker of T-cell differentiation, as a predictive correlate of response to ICI therapy. Successful treatment of tumor-bearing mice with ICI increases the frequency and T-cell receptor clonality of the peripheral CX3CR1+CD8+ T-cell subset that includes an enriched repertoire of tumor-specific and tumor-infiltrating CD8+ T cells. Furthermore, an increase in the frequency of the CX3CR1+ subset in circulating CD8+ T cells early after initiation of anti-PD-1 therapy correlates with response and survival in patients with non-small cell lung cancer. Collectively, these data support T-cell CX3CR1 expression as a blood-based dynamic early on-treatment predictor of response to ICI therapy.

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.

Tumor inflammatory signature as a biomarker of response to immunotherapy in lung cancer

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Background: Tumor Inflammation signatures (TIS) comprising multiple immune genes have been shown to enrich for response to ICI. To study this immune phenotype in a large cohort of clinically evaluated patients, we studied gene expression data for a stable pan-cancer tumor inflammation profile and clinical response to ICI. Methods: 1323 FFPE tumors from 35 histologies were tested by RNA-seq, PD-L1 IHC and DNA-seq for TMB. Unsupervised analysis of the RNA-seq data revealed a cluster of 160 genes which separated inflamed from non-inflamed tumor microenvironments (TME). A TIS, algorithmically defined as the mean mRNA expression of the 160 genes was developed with each tumor assigned into a weak, moderate or strong inflammation group. PD-L1 IHC was performed using DAKO 22C3 antibody and considered positive if TPS ≥1%. TMB > 10 mut/Mb was considered high. The TIS, PD-L1 and TMB were independently applied to 110 NSCLC cases for association with ORR to ICIs by RECIST criterion. Results: Unsupervised clustering identified 3 inflammation clusters in the 1323 samples; inflamed (n = 439; 33.2%), borderline (n = 467; 35.3%) and non-inflamed (n = 417; 31.5%). 160 genes are over-represented by T & B-cell activation, IFNg, chemokine, cytokine and interleukin pathways. The TIS algorithm results in an inflammatory score that leads to 3 distinct groups of strong (n = 384; 29.0%), moderate (n = 354; 26.8%) and weak (n = 585; 44.2%) inflammation. Strongly inflamed tumors are over-represented by PD-L1+ tumors (240/384) whereas weakly inflamed tumors are significantly under-represented by PD-L1+ tumors (369/585; p = 1.02e-14). Strongly inflamed tumors presented with improved ORR to ICI in NSCLC (36.6%; 16/44; p = 0.051). Similar results were observed for overall survival for strongly inflamed tumors (median = 16 months; p = 0.0012) vs. weakly inflamed tumors (median = 8 months). ORR for PD-L1+ 33.96% (p = 0.026) and TMB high 21.43% (p = 0.83) were observed. Conclusions: Concurrent measurement of multiple markers led to a comprehensive, stable TIS that predicts host immune response. A strongly inflamed TIS was associated with higher ORR versus single biomarker PD-L1 and TMB in NSCLC.

Inflammation and cell proliferation signatures: Implications for response to immune checkpoint inhibition therapies

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Background: Progress in unraveling the complex tumor immune microenvironment (TIME) has aided our understanding of the host immune response to ICI therapies. To gain further insight, we associate a 160-gene tumor inflammation signature (TIS) with cell proliferation status and response to ICI. Methods: 242 FFPE tumor samples from lung, RCC and melanoma were evaluated by RNA-seq to measure expression levels of 394 immune related genes. TIS (weak, moderate, strong) and cell proliferation status (poor, moderate, high) were determined by algorithmic analysis of selected gene pathways. All cases were evaluated for association with ORR to ICIs using RECIST criterion. Furthermore, 13 pre-post ICI treated biopsy pairs were studied to understand the dynamics of these signatures following treatment. Results: In both weakly and moderately inflamed tumors, ORR was highest in moderately proliferative tumors 32.6% (15/46) and 37.8% (14/37), respectively (Table). Surprisingly, in strongly inflamed tumors, both highly and moderately proliferative tumors had a high response rate of 55% (11/20) and 43.2% (16/37), whereas poorly proliferative tumors have a significantly lower response rate of 12.5% (3/24; p= 0.03). 6 of 13 pre-post ICI treated cases demonstrated increased inflammation post treatment, with 83% (5/6) demonstrating concurrent decrease in cell proliferation. Conclusions: Together, TIS and cell proliferation predict response to ICI in NSCLC, RCC and melanoma. The data suggests that in strongly inflamed and highly proliferative tumors, the cell proliferation signal could be attributed to antigen stimulated T-cell proliferation, whereas in other categories of inflammation, moderately proliferative tumors contain signal from both immune cells and tumor cells. Further studies are required to determine the relationship between these signatures in hot and cold tumors. [Table: see text]

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1-3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10-18.

TCR Convergence in Individuals Treated With Immune Checkpoint Inhibition for Cancer

Tumor antigen-driven selection may expand T cells having T cell receptors (TCRs) of shared antigen specificity but different amino acid or nucleotide sequence in a process known as TCR convergence. Substitution sequencing errors introduced by TCRβ (TCRB) repertoire sequencing may create artifacts resembling TCR convergence. Given the anticipated differences in substitution error rates across different next-generation sequencing platforms, the choice of platform could be consequential. To test this, we performed TCRB sequencing on the same peripheral blood mononuclear cells (PBMC) from individuals with cancer receiving anti-CTLA-4 or anti-PD-1 using an Illumina-based approach (Sequenta) and an Ion Torrent-based approach (Oncomine TCRB-LR). While both approaches found similar TCR diversity, clonality, and clonal overlap, we found that Illumina-based sequencing resulted in higher TCR convergence than with the Ion Torrent approach. To build upon this initial observation we conducted a systematic comparison of Illumina-based TCRB sequencing assays, including those employing molecular barcodes, with the Oncomine assay, revealing differences in the frequency of convergent events, purportedly artifactual rearrangements, and sensitivity of detection. Finally, we applied the Ion Torrent-based approach to evaluate clonality and convergence in a cohort of individuals receiving anti-CTLA-4 blockade for cancer. We found that clonality and convergence independently predicted response and could be combined to improve the accuracy of a logistic regression classifier. These results demonstrate the importance of the sequencing platform in assessing TCRB convergence.

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.

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.

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.

TAp73 expression and P1 promoter methylation, a potential marker for chemoresponsiveness to cisplatin therapy and survival in muscle-invasive bladder cancer (MIBC)

Intrinsic and/or acquired resistance to cisplatin is a significant obstacle in the treatment of muscle-invasive bladder cancer. p73, a p53 homolog and determinant of chemosensitivity, is rarely mutated in bladder cancer (BC). However p73 expression and therefore function can be repressed through epigenetic changes. In this study, we sought to identify DNA methylation status of p73, expression of TAp73 isoform, and their role in cisplatin sensitivity in BC. Primary tumor samples from 338 bladder cancer patients showed decreased TAp73 expression in MIBC compared to superficial BC. Low TAp73 protein expression was associated with shorter overall survival. To investigate if the loss of expression was methylation dependent, we utilized Illumina 450K methylation arrays to interrogate over 150 BC patient samples. We found 12 distinct CpGs in the p73 gene locus that were hypermethylated in tumors compared to adjacent normal tissues. Patients with high p73 promoter methylation specifically at CpG site cg07382920 had worse survival. In vitro, treatment with a DNA demethylating agent, decitabine (DAC), decreased TAp73 methylation and upregulated expression in both CR-T24 (cisplatin resistant T24 cells) and wild type T24 cells. Furthermore, treatment with DAC increased cisplatin response in wild type T24 and CR-T24. Our studies indicate that TAp73 expression and P1 promoter methylation, specifically at the cg073892920 site, may have prognostic and diagnostic value in MIBC. In the setting of P1 promoter hypermethylation, DAC could be used as a potentiating agent of cisplatin-based chemotherapy.

The tumor microenvironment in EGFR-driven loco-regional lung adenocarcinoma can predict higher risk of recurrence

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Background: The role of EGFR tyrosine kinase inhibitors (TKIs) as adjuvant therapy in EGFR-mutated NSCLC is still controversial. Identifying biomarkers associated with increased risk of recurrence may help stratify pts & guide adjuvant therapy. We hypothesized that tumor immune microenvironment (TME) alterations could predict disease-free survival (DFS) in these pts. Methods: The Cancer Genome Atlas (TCGA) lung Adenocarcinoma (LUAD) data at Genomic Data Common (GDC) was accessed for pt phenotype, updated outcome & normalized gene expression profile (RNA seq). Immune landscape data was obtained from PANCAN. We chose to focus on 54 key TME genes, identified from a commercially available immune report card from OmniSeq (Inc.). Pt groups were divided via K-mean clustering. Group comparison was done via Likelihood Ratio (LR, categorical), Mann Whitney (continuous), log-rank (survival) & Cox regression (outcome). Bonferroni correction was used to correct for multiple comparisons. Results: 877 pts with LUAD were identified, 32 of whom had EGFR mutations and were at stages I to III. The mutations were mostly in the TK domain, involving exons 18 (12%), 19 (27%), 20 (6%), & 21 (33%). Only 3% harbored the T790M mutation. None of the pts received adjuvant TKI. Analysis of the impact of individual genes on DFS yielded a group of 8 genes whose high expression was associated with improved DFS: IL10 (HR 0.58, p 0.029), BTLA (HR 0.66, p 0.07), CD8A (HR 0.6252, p 0.099), CD39 (HR 0.454, p 0.037), CCR2 (HR 0.729, p 0.039), CSF1R (HR 0.70, p 0.087), ICOS (HR 0.66, p 0.062), & CD4 (HR 0.67, p 0.059). K-mean clustering of the pts using these genes demonstrated 2 groups with distinct immune profiles. Group 1 was characterized by higher leukocyte and stromal fractions, lymphocyte infiltration score, macrophage regulation, TGF-ß response, & T cell richness with less proliferation, pointing towards a more “inflamed” phenotype. Significant difference between the two groups in the immune subtypes was found (LR 10, p = 0.039). 90% of pts in the inflamed group had tumors with IFN-γ dominant, inflammatory, and TGF-ß dominant subtypes, while 45% of the “non-inflamed” group had lymphocyte depleted & wound healing signatures. DFS was significantly longer in the inflamed group (median DFS 1480 vs 772 days, p = 0.002). Conclusions: In pts with resected EGFR-mutated LUAD, an inflamed TME is associated with prolonged DFS. Identifying these pts may help select those who would benefit from adjuvant therapy.

Evaluation of tumor microenvironment and biomarkers of immune checkpoint inhibitor (ICI) response in metastatic renal cell carcinoma (mRCC)

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Background: ICIs are now standard of care for mRCC; however, there are few biomarkers to predict ICI response. Recent data from atezolizumab/bevacizumab trials in mRCC suggest tumors with high Teffhigh/PD-L1+ are more likely to respond to ICI. Here, we use two gene panels as well as other inflammation markers in the tumor microenvironment to correlate with ICI responses. Methods: This multicenter study evaluated 86 patients (pts) with mRCC treated with ICIs. FFPE tumor samples were evaluated by RNA sequencing for Teff status. Two gene panels were analyzed: a Teff Gene Panel (CD8, CD27, IFNG, GZMA, GZMB, PRF1, EOMES, CXCL9, CXCL10, CXCL11, CD274, CTLA4, FOXP3, TIGIT, IDO1, PSMB9, TAP1) and a 5-Gene panel (FOXP3, CCR4, KLRK1, ITK, and TIGIT) based on the gene expression pattern of tumors in our cohort. Objective response rates (ORRs, defined as CRs and PRs) were correlated with PD-L1 status (positivity was defined as ≥1% TPS based on Dako 22C3 IHC assay), and TMB (0-10, 10-20, ≥20 mut/Mb), and tumor inflammation (high CD8 expression compared to a large reference population). Best responses to ICI was determined by an expert radiologist using RECIST 1.1 criteria. Inflamed tumor status, Teff gene panel, 5-gene panel, PD-L1 status, and TMB were associated with ORR and tested using a chi-squared test with Yates’s continuity correction. Results: ORR was 50% (4/8) for PD-L1 positive pts and 14% (9/65) for PD-L1 negative pts (p = 0.042). The majority of tumors (95%, 82/86) had TMB < 10 mut/mb. 43 pts (50%) were classified as Teffhigh and 43 pts were classified as Tefflow. ORR was 23% (10/43) in the Teffhigh cohort and 12% (5/43) in the Tefflow cohort (p = 0.256). ORR was 31% (14/45) in the 5-Gene high cohort and 2% (1/41) in the 5-Gene low cohort (p = 0.001). Conclusions: TMB and tumor inflammation based on CD8 did not reliably predict for objective responses in this study of mRCC pts treated with ICIs. Gene expression signatures provide a more comprehensive evaluation of the tumor microenvironment and may lead to better predictive biomarkers for ICI response than individual biomarkers such as PD-L1, TMB, or CD8 expression.

Validation of Melanoma Immune Profile (MIP), a Prognostic Immune Gene Prediction Score for Stage II-III Melanoma

PURPOSE

Biomarkers are needed to stratify patients with stage II-III melanoma for clinical trials of adjuvant therapy because, while immunotherapy is protective, it also confers the risk of severe toxicity. We previously defined and validated a 53-immune gene melanoma immune profile (MIP) predictive both of distant metastatic recurrence and of disease-specific survival (DSS). Here, we test MIP on a third independent population.

EXPERIMENTAL DESIGN

A retrospective cohort of 78 patients with stage II-III primary melanoma was analyzed using the NanoString assay to measure expression of 53 target genes, and MIP score was calculated. Statistical analysis correlating MIP with DSS, overall survival, distant metastatic recurrence, and distant metastasis-free interval was performed using ROC curves, Kaplan-Meier curves, and standard univariable and multivariable Cox proportional hazards models.

RESULTS

MIP significantly distinguished patients with distant metastatic recurrence from those without distant metastatic recurrence using ROC curve analysis (AUC = 0.695; P = 0.008). We defined high- and low-risk groups based on the cutoff defined by this ROC curve and find that MIP correlates with both DSS and overall survival by ROC curve analysis (AUC = 0.719; P = 0.004 and AUC = 0.698; P = 0.004, respectively). Univariable Cox regression reveals that a high-risk MIP score correlates with DSS (P = 0.015; HR = 3.2).

CONCLUSIONS

MIP identifies patients with low risk of death from melanoma and may constitute a clinical tool to stratify patients with stage II-III melanoma for enrollment in clinical trials.

Vitamin D3 enhances the response to cisplatin in bladder cancer through VDR and TAp73 signaling crosstalk

Background

Vitamin D₃ (VitD) deficiency is linked to increased incidence and worse survival in bladder cancer (BCa). In addition to cystectomy, patients are treated with cisplatin‐based chemotherapy, however 30%‐50% of patients do not benefit from this treatment. The effects of VitD deficiency on response to chemotherapy remain unknown.

Methods

To test effects of VitD supplementation on the response to cisplatin we analyzed patient serum VitD levels and correlated that with survival. In vivo, VitD deficient mice were treated with cisplatin, with or without pretreatment with the active VitD metabolite, 1,25 dihydroxyvitamin D₃ (1,25D₃). Lastly, using BCa cell lines, T24 and RT‐112, the mechanism of action of 1,25D₃ and cisplatin combination treatment was determined by apoptosis assays, as well as western blot and RT‐PCR.

Results

In this study, we determined that low serum 25 hydroxyvitamin D₃ (25D₃) levels was significantly associated with worse response to cisplatin. Pretreating deficient mice with 1,25D₃, reduced tumor volume compared to cisplatin monotherapy. In vitro, 1,25D₃ pretreatment increased the apoptotic response to cisplatin. 1,25D₃ pretreatment increased expression of TAp73 and its pro‐apoptotic targets, in a VDR dependent manner. VDR and its transcriptional targets were induced after 1,25D₃ treatment and further increased after the combination of 1,25D₃ and cisplatin in a TAp73 dependent manner.

Conclusions

Our data suggest that VitD deficiency could be a biomarker for poor response to cisplatin, and pretreating with VitD can increase the apoptotic response to cisplatin through VDR and TAp73 signaling crosstalk.

Identification of targets for prostate cancer immunotherapy

BACKGROUND

We performed profiling of the immune microenvironment of castration-resistant (CRPC) and castration-sensitive (CSPC) prostate cancer (PC) in order to identify novel targets for immunotherapy.

METHODS

PD-L1 and CD3/CD8 immunohistochemistry, PD-L1/2 fluorescent in situ hybridization, tumor mutation burden, microsatellite instability, and RNA-seq of 395 immune-related genes were performed in 19 CRPC and CSPC. Targeted genomic sequencing and fusion analysis were performed in 17 of these specimens.

RESULTS

CD276, PVR, and NECTIN2 were highly expressed in PC. Comparison of CRPC versus CSPC and primary versus metastatic tissue revealed the differential expression of immunostimulatory, immunosuppressive, and epithelial-to-mesenchymal transition (EMT)-related genes. Unsupervised clustering of differentially expressed genes yielded two final clusters best segregated by CRPC and CSPC status.

CONCLUSION

CD276 and the alternative checkpoint inhibition PVR/NECTIN2/CD226/TIGIT pathway emerged as relevant to PC checkpoint inhibition target development.

Evaluation of tumor microenvironment and biomarkers of immune checkpoint inhibitor (ICI) response in metastatic renal cell carcinoma (mRCC)

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Background: ICIs are now standard of care for mRCC; however, there are few biomarkers to predict ICI response. Recent data from atezolizumab/bevacizumab trials in mRCC suggest tumors with high Teffhigh/PD-L1+ are more likely to respond to ICI. Here, we use this Teff gene panel as well as other markers of inflammation in the tumor microenvironment to correlate with ICI responses. Methods: This multicenter study evaluated 69 pts with mRCC treated with ICIs. FFPE tumor samples were evaluated by RNA sequencing to measure transcript levels of genes related Teff status. Teff status was defined as the mRNA expression of 17 genes (CD8, CD27, IFNG, GZMA, GZMB, PRF1, EOMES, CXCL9, CXCL10, CXCL11, CD274, CTLA4, FOXP3, TIGIT, IDO1, PSMB9, TAP1), with Teffhigh/low separated at the median. PD-L1 positivity was defined as ≥1% TPS based on Dako 22C3 IHC assay, and TMB high as > 10 mutations per megabase. Inflamed tumors were defined as CD8 expression in the top 75th percentile compared to a large reference population of multiple tumor types. Best responses to ICI was determined by an expert radiologist using RECIST 1.1 criteria. Inflamed tumor status, Teff gene expression, PD-L1 positive, and TMB were associated with disease control (DC, defined as CR, PR, or stable disease). DC comparisons were tested using a chi-squared test with Yates’s continuity correction. Results: DC was 63% (5/8) amongst PD-L1 positive pts and 52% (31/60) in PD-L1 negative patients (p = 0.84). Only 2 pts were TMB high. The majority of mRCC tumors (97%, 67/69) were TMB low. 6-month DC in TMB high tumors was 50% (1/2) and 49.3% (33/67) in TMB low tumors (p = 1.0). 36 pts were classified as Teffhigh and 33 patients were classified as Tefflow. 6-month DC was 61% (22/36) in the Teffhigh cohort and 36% (12/33) in the Tefflow cohort (p = 0.069). 6-month DC was 64% of inflamed tumors (16/25) vs 41% of non-inflamed tumors (18/44) (p = 0.111). Conclusions: TMB high and PD-L1 expression do not reliably predict for DC in pts with mRCC. Utilizing a gene signature score may better predict ICI response.

Tumor mutational burden (TMB): Assessment of inter- and intra-tumor heterogeneity

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Background: As an emerging biomarker, a high TMB is associated with response to immune checkpoint inhibitors. The tissue selected for molecular analysis could be critical for accurate TMB assessment and therapeutic selection. We evaluated TMB and the tumor specimen tested to determine the extent tissue selection has on TMB analysis. Methods: TMB profiling was performed on 73 cases representing 8 tumor types. 8 patients with multiple specimens from the same surgical event were evaluated for intra-tumor heterogeneity, and 20 patients with specimens from multiple surgical events spanning up to seven years were tested for inter-tumor heterogeneity. Two to six specimens, including primary, recurrent and metastatic cases, were evaluated per patient. For each patient, TMB values within and between tumors were assessed for concordance using a clinically relevant TMB-high cutoff of ≥ 10 mutations/Mb. Results: TMB values ranged from 0 – 58, with 7 cases scored as TMB-high. One patient with a primary skin melanoma and a lung metastasis biopsied after 34 months was concordant for TMB-high. For 19 patients (76%), all samples were concordant for TMB-low. For intratumor testing, 2 of 8 (25%) patients had discordant specimens (crossed the TMB-cutoff). The first patient had 4 intra-tumor CRC samples with TMB values of 10.6, 10.7, 9.7 and 9.7. The second patient had 5 intra-tumor pancreatic samples with TMB values of 10.7, 4.4, 6.2, 8.8, 7.9. Of the patients with 20 inter-tumor samples, 2 patients (each with melanoma) had discordant TMB-high calls. One had a lymph node metastasis TMB of 12.3 and a liver metastasis collected five months later with a reduced TMB of 0.9. In contrast, the second discordant melanoma patient had a peritoneum metastasis with an elevated TMB of 11.4 collected 14 months after a mesentery metastasis with a TMB of 8.7. Conclusions: TMB variation within tumors and between tumors from different surgical events occurs equally and in 17% of patients. This clinical tumor heterogeneity on the inter- or intra-tumor level may limit the utility and the application of TMB at a cutoff of 10. A careful analysis of tissues to enrich for neoplastic cells may improve assay sensitivity and increase analytical accuracy at this precise cut point.

Cell proliferation as a biomarker for response to immune checkpoint inhibitors in highly inflamed renal cell carcinoma

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Background: Cell proliferation is an important marker of survival in many tumors and we hypothesized that this attribute could be related to response to immune checkpoint inhibitors in RCC. Previously we reported (SITC 2018) moderately proliferative lung cancer has a much higher response rate than either poorly or highly proliferative tumors. Methods: 69 FFPE tumor samples of RCC were evaluated by RNA-seq to measure transcript levels of 394 immune related genes, including 10 related to cell proliferation (BUB1, CCNB2, CDK1, CDKN3, FOXM1, KIAA0101, MAD2L1, MELK, MKI67, TOP2A). Cell proliferation, defined as the mean mRNA expression of these 10 genes was evaluated for association with ORR to ICIs by RECIST v1.1 criteria for both PD-L1 IHC positive and negative cases. Cell proliferation for each case was split into 3 tertiles of poorly ( < 33), moderately (33-66) and highly ( > 66) proliferative compared to a reference population. Poorly and highly proliferative were grouped for comparison to moderately proliferative tumors. Tumors were inflamed or non-inflamed based upon RNA‐seq analysis of CD8 compared to a reference population of more than 500 cases of multiple tumors. Non-inflamed, or immune desert tumors, defined as the lower 25th percentile of rank for CD8+ T-cells, and greater than 75th percentile of rank as inflamed. Results: In our cohort of 69 patient the overall ORR was 18.8%. 15.9% of tumors were non-inflamed with an ORR of 9.1%. For 36.2% inflamed tumor the ORR was 32%. For cell proliferation 62.2% were poorly proliferative, 8.7% were highly proliferative, and 29% were moderately. ORR in moderately proliferative tumors was 30% versus 14.2% in poorly/highly proliferative tumors. In inflamed tumors, ORR in moderately proliferative tumors was 37.5% as opposed to 17.6% in poorly/highly proliferative tumors. In 11 non-inflamed tumors, there was only one responder, which was a poorly/highly proliferative tumor. Conclusions: Cell proliferation may play a crucial role in distinguishing RCC patients who may have a clinical benefit to ICI, including the important subgroup of inflamed tumors. Moderately proliferative tumors have a higher ORR than their poorly/highly counterparts.

Cell proliferation as a biomarker for response to immune checkpoint inhibitors in PD-L1 negative renal cell carcinoma

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Background: Cell proliferation is an important marker of survival in many tumors, and we hypothesized that this attribute could be related to response to immune checkpoint inhibitors (ICIs) in RCC. Previously we reported (SITC 2018) that moderately proliferative lung cancer have a much higher response rate than either poorly or highly proliferative tumors. Methods: 69 FFPE RCC tumor samples were evaluated by RNA-seq to measure transcript levels of 394 immune related genes. Cell proliferation was defined as the mean mRNA expression of 10 genes (BUB1, CCNB2, CDK1, CDKN3, FOXM1, KIAA0101, MAD2L1, MELK, MKI67, TOP2A) which was evaluated for association with ORR to ICIs by RECIST v1.1 criteria for both PD-L1 IHC positive and negative cases. Cell proliferation for each case was split into 3 tertiles of poorly ( < 33), moderately (33-66) and highly ( > 66) proliferative versus a reference population. Poorly and highly proliferative were grouped for comparison to moderately proliferative tumors. PD-L1 IHC was performed using DAKO 22C3 antibody and scored by FDA guidelines and considered positive if TPS ≥1% and negative if < 1%. Results: In our cohort of 69 patients, the overall ORR was 18.8. The majority, 91% of tumors were PD-L1 negative, with ORR of 14.8%, as opposed to ORR of 50% in PD-L1 positive cases. 62.2% of tumors were poorly proliferative, 8.7% were highly proliferative, and 29% were moderately proliferative. ORR in moderately proliferative tumors was 30% and 14.2% in poorly/highly proliferative tumors. In PD-L1 negative tumors the ORR in moderately proliferative tumors was 20% and 13% in poorly/highly proliferative tumors. For the 5 moderately proliferative, PD-L1 positive tumors, there were 2 PR and 1 CR, and in the 3 poorly/highly proliferative tumors there was 1 PR. Conclusions: Cell proliferation may play a crucial role in distinguishing RCC patients who may have a clinical benefit to ICI, including the important subgroup of PD-L1 negative tumors. Moderately proliferative tumors have a higher ORR than their poorly/highly counterparts.

RNA-sequencing reveals immunotherapy targets in gynecological cancer

8

Background: We performed microsatellite instability testing and expression immune profiling of endometrioid and serous carcinomas to identify immunotherapeutic targets and histologic attribute correlates. Methods: Microsatellite instability and RNA-seq of 395 immune-related genes were performed in 37 endometrioid and 53 serous carcinomas. Each gene was ranked against a reference population and subsequently compared to a separate clinical database reference of diverse neoplasms to perform Wilcoxon ranked sum test comparisons. Benjamin-Hochberg corrected p-values are reported. Results: VTCN1, IDO1, LAG3, and components of the mTOR/AKT1 pathway were overexpressed in both endometrioid and serous carcinomas compared to the clinical database population. CD276 and NT5E were uniquely overexpressed in the endometrioid set (Table). In the endometrioid set ADGRE5 was overexpressed in endometrioid primaries when compared to their metastatic counterparts. Serous metastases relatively overexpressed HLA-DPA1 compared to their primary counterparts. Ten of 26 endometrioid cancers with available microsatellite instability status were microsatellite unstable. All serous carcinomas were microsatellite stable. There was no correlation between microsatellite instability status and expression of any gene in either endometrioid or serous cancers. Conclusions: We identified high RNA-expression of VTCN1, IDO1, CD276, and LAG3 in endometrioid and serous carcinomas while NT5E (ADORA2A ligand) was found to be uniquely upregulated in endometrioid carcinomas. These markers may play a role in immune suppression in gynecological cancers and are potential immunotherapeutic targets. The upregulation of ADGRE5 in primary endometrioid cancers and upregulation of HLA-DPA1 in metastatic serous cancers suggests immunologic differences which may be relevant to the formation of metastatic disease.

Evaluation of tumor microenvironment and biomarkers of immune checkpoint inhibitor (ICI) response in metastatic renal cell carcinoma (mRCC)

607

Background: ICIs are now standard of care for mRCC; however, there are few biomarkers to predict ICI response. Recent data from atezolizumab/bevacizumab trials in mRCC suggest tumors with high Teffhigh/PD-L1+ are more likely to respond to ICI. Here, we use this Teff gene panel as well as other markers of inflammation in the tumor microenvironment to correlate with ICI responses. Methods: This multicenter study evaluated 69 pts with mRCC treated with ICIs. FFPE tumor samples were evaluated by RNA sequencing to measure transcript levels of genes related Teff status. Teff status was defined as the mRNA expression of 17 genes (CD8, CD27, IFNG, GZMA, GZMB, PRF1, EOMES, CXCL9, CXCL10, CXCL11, CD274, CTLA4, FOXP3, TIGIT, IDO1, PSMB9, TAP1), with Teffhigh/low separated at the median. PD-L1 positivity was defined as ≥1% TPS based on Dako 22C3 IHC assay, and TMB high as > 10 mutations per megabase. Inflamed tumors were defined as CD8 expression in the top 75th percentile compared to a large reference population of multiple tumor types. Best responses to ICI was determined by an expert radiologist using RECIST 1.1 criteria. Inflamed tumor status, Teff gene expression, PD-L1 positive, and TMB were associated with disease control (DC, defined as CR, PR, or stable disease). DC comparisons were tested using a chi-squared test with Yates’s continuity correction. Results: DC was 63% (5/8) amongst PD-L1 positive pts and 52% (31/60) in PD-L1 negative patients (p = 0.84). Only 2 pts were TMB high. The majority of mRCC tumors (97%, 67/69) were TMB low. 6-month DC in TMB high tumors was 50% (1/2) and 49.3% (33/67) in TMB low tumors (p = 1.0). 36 pts were classified as Teffhigh and 33 patients were classified as Tefflow. 6-month DC was 61% (22/36) in the Teffhigh cohort and 36% (12/33) in the Tefflow cohort (p = 0.069). 6-month DC was 64% of inflamed tumors (16/25) vs 41% of non-inflamed tumors (18/44) (p = 0.111). Conclusions: TMB high and PD-L1 expression do not reliably predict for DC in pts with mRCC. Utilizing a gene signature score may better predict ICI response.

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.

Electronic supplementary material

The online version of this article (10.1186/s40425-019-0506-3) contains supplementary material, which is available to authorized users.

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.

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.

Analysis of mutations in primary and metastatic synovial sarcoma

Synovial sarcoma is the most common pediatric non-rhabdomyosarcoma soft tissue sarcoma and accounts for about 8-10% of all soft tissue sarcoma in childhood and adolescence. The presence of a chromosomal translocation-associated SS18-SSX-fusion gene is causally linked to development of primary synovial sarcoma. Metastases occur in approximately 50-70% of synovial sarcoma cases with yet unknown mechanisms, which led to about 70-80% mortality rate in five years. To explore the possibilities to investigate metastatic mechanisms of synovial sarcoma, we carried out the first genome-wide search for potential genetic biomarkers and drivers associated with metastasis by comparative mutational profiling of 18 synovial sarcoma samples isolated from four patients carrying the primary tumors and another four patients carrying the metastatic tumors through whole exome sequencing. Selected from the candidates yielded from this effort, we examined the effect of the multiple missense mutations of ADAM17, which were identified solely in metastatic synovial sarcoma. The mutant alleles as well as the wild-type control were expressed in the mammalian cells harboring the SS18-SSX1 fusion gene. The ADAM17-P729H mutation was shown to enhance cell migration, a phenotype associated with metastasis. Therefore, like ADAM17-P729H, other mutations we identified solely in metastatic synovial sarcoma may also have the potential to serve as an entry point for unraveling the metastatic mechanisms of synovial sarcoma.

Budget Impact of Next-Generation Sequencing for Molecular Assessment of Advanced Non-Small Cell Lung Cancer

BACKGROUND

Genetic testing for nonsquamous advanced non-small cell lung cancer (aNSCLC) is recommended to guide first-line therapy. Activating mutations can be identified via single-gene testing or next-generation sequencing (NGS).

OBJECTIVES

To evaluate the budget impact of NGS instead of single-gene testing for tissue-based molecular assessment of aNSCLC from the US health care payer perspective.

METHODS

An annual cohort of newly diagnosed patients with nonsquamous aNSCLC in a hypothetical 1-million-member health care plan was evaluated using a Markov model over 5 years. Epidemiology and testing rates (EGFR, ALK, ROS1, BRAF, MET, HER2, and RET) were from the literature. Treatments were determined by available genetic information. Safety, progression, and survival with targeted therapy or chemotherapy were from randomized clinical trials. Single-gene testing and first-line and maintenance treatment costs were from RED BOOK and Medicare fee schedules; NGS testing, adverse event, and progression costs to payers were from the literature.

RESULTS

Three hundred sixteen testing-eligible patients with aNSCLC were expected annually, of whom 179 undergo genetic testing. Of 57 patients expected to have activating mutations, single-gene testing identified 35, whereas NGS identified 54. NGS, instead of single-gene testing, decreased expected testing procedure-related costs to the health plan payer by $24,651. First-line and maintenance treatment costs increased by $842,205, offset by a $385,000 decrease in second-line treatment and palliative care costs. Over 5 years, total budget impact was $432,554 ($0.0072 per member per month).

CONCLUSIONS

NGS is expected to identify more patients with activating mutations, thereby better enabling selection for targeted therapy and clinical trial enrollment. The budget impact to US payers is expected to be minimally cost-additive.