Abstract 3404: Landscape and genomic correlates of ctDNA-based tumor mutational burden across six solid tumor types

4533 Background: We performed a CGP to compare the genomic alterations (GA) in ABC, UBC and SCCB. Methods: 143 cases of ACB, 2,142 cases of UCB and 83 cases of SCCB were subjected to CGP using a hybrid-capture based assay. Tumor mutational burden (TMB) was determined on 1.1 Mbp of sequenced DNA and microsatellite instability (MSI) was determined on 114 loci. PD-L1 expression was determined by IHC. Results: ABC patients were younger and more often female than UBC and SCCB (P < 0.0001). UBC and SCCB had a higher GA/tumor than ABC (P = 0.01). Un-targetable GA were similar in all 3 groups involving TP53 and KRAS. APC GA were more frequent in ABC whereas TERT, CDKN2A/B and DNA-repair genes ( ARID1A and KDM6A) more frequently altered in UBC and SCCB. Targetable MTOR pathway GA ( PIK3CA, TSC1, PTEN) were more frequent in UBC and SCCB as were targetable kinase alterations ( FGFR3 and ERBB2). The UBC and SCCB had a significantly higher TMB than ABC (P < 0.0001) including mean TMB and TMB > 20 mut/Mb (P < 0.0001). CD274 (PD-L1) was amplified more frequently in SCCB than ACB or UBC (P < 0.0001). MSI high status was very uncommon in all tumor types. Conclusions: Deep sequencing reveals that ABC features a widely different genomic profile from UBC and SCCB. UBC has the highest frequencies of targetable kinase GA and high TMB. SCCB has the highest frequencies of IO efficacy predicting biomarkers including mean TMB and PD-L1 amp. Nonetheless, ABC does feature potential kinase targets such as FGFR3 and ERBB2. [Table: see text]

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A model based adjustment for tumor mutational burden across different tumor types

Annals of Oncology ◽

10.1093/annonc/mdx509.004 ◽

2017 ◽

Vol 28 ◽

pp. vii13 ◽

Cited By ~ 1

Author(s):

M.H. Wang ◽

W.W. Shi ◽

P. Zhang ◽

S.H. Zhao ◽

J.Y. Cao ◽

...

Keyword(s):

Model Based ◽

Mutational Burden ◽

Tumor Mutational Burden ◽

Tumor Types

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FGFR2: A pan-genomic target.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.15_suppl.3099 ◽

2019 ◽

Vol 37 (15_suppl) ◽

pp. 3099-3099

Author(s):

Russell Madison ◽

Ethan Sokol ◽

Alexa Betzig Schrock ◽

Adrienne Johnson ◽

Dean Pavlick ◽

...

Keyword(s):

Copy Number ◽

High Status ◽

Breast Carcinomas ◽

Gi Tract ◽

Mutational Burden ◽

Tumor Mutational Burden ◽

Small Cohort ◽

Copy Number Changes ◽

Investigational Agents ◽

Tumor Types

3099 Background: FGFR2 genomic alterations (GA) have been described in a variety of solid tumors and emerged as biomarkers for investigational agents undergoing clinical trials. Methods: 201,766 primarily relapsed/refractory malignancies were evaluated with a hybrid-capture based sequencing assay Tumor mutational burden (TMB) was determined on 0.8-1.1 Mbp of sequenced DNA and reported as mut/Mb. Microsatellite instability (MSI) was determined on 114 loci. PD-L1 expression was determined by IHC (Dako 22C3 antibody). Results: FGFR2 GA were detected in 2,993 (1.5%) cases featuring short variant (SV) mut (42%), copy number changes (27%), rearrangements/fusions (28%) and multiple GA (3%). The most frequent SV GA were S252W, N549K, C382R, P253R, Y375C, K659E and R664W. A small cohort (2%) of tumors featured the V564I and V564L GA that are associated with resistance to TKI drugs. The FGFR2-altered cases were 69% female/31% male with median age of 61 yrs. Most frequent GA in FGFR2 altered cancers: TP53 (47%), PIK3CA (22%), PTEN (20%), ARID1A (18%), CDKN2A/2B (18/14%) and MYC (12%). FGFR2 SVs most common in endometrial, breast carcinomas (ca) and CUP. FGFR2 amplification most common in breast, gastroesophageal and lung ca. FGFR rearrangement/fusions most common in cholangioca (37%), CUP (15%), pancreatobiliary (12%) and breast ca (6%). The FGFR2- BICC1 was the most frequent fusion followed by fusions with TACC2, AHCYL1, CCDC6, VCL, and KIAA1217. MSI-High status present in 6.8% of evaluable FGFR2 altered cases (63% in endometrial ca). Median TMB was 3.5 mut/Mb with 21.8% featuring ≥ 10 mut/Mb and 12.0% featuring ≥ 20 mut/Mb. Only 63% of MSI-High FGFR2 mut tumors had TMB ≥ 20 mut/Mb. 12.7% FGFR2 mut+ had > 1% PD-L1 staining with 3.4% > 50% staining. 29% of PD-L1 IHC+ cases in NSCLC. FGFR mut ca’s responding to anti-FGFR2 therapies will be presented. Conclusions: FGFR2 GA are most frequent in cholangioca, breast, GI tract, lung ca and CUP, with enrichment of FGFR2 fusions in biliary tract ca. Cases with FGFR2 GA typically do not feature other kinase driver GA and are associated with mut in the MTOR/PIK3CA/AKT pathways. Finally, in contrast with RTK driver GA in EGFR (5.7%) and ERBB2 (7.9%), at 12.0%, across all tumor types, FGFR2 mut cancers may have higher frequency of TMB ≥ 20 mut/Mb suggesting potential immunotherapy responsiveness.

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The landscape of ARID1A variants and correlation with tumor mutational burden in Chinese solid tumor patients.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.15_suppl.e14624 ◽

2019 ◽

Vol 37 (15_suppl) ◽

pp. e14624-e14624

Author(s):

Jia Wei ◽

JieJie Zhang ◽

Qiang Wen ◽

Xiaoyi Zhu ◽

Dapeng Li ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Squamous Cell ◽

Lung Carcinoma ◽

Solid Tumor ◽

Immune Checkpoint ◽

Squamous Cell Lung Carcinoma ◽

Tumor Patients ◽

Cell Lung Carcinoma ◽

Mutational Burden ◽

Tumor Mutational Burden

e14624 Background: ARID1A (the AT-rich interaction domain 1A) is one of the most commonly mutated genes in cancer, mostly caused by frameshift variants. Here, we describe the mutational landscape of ARID1A in Chinese cancer patients and its correlation with tumor mutational burden (TMB). Methods: Formalin fixed paraffin embedded (FFPE) samples of 3,828 Chinese solid tumor patients were collected for next‐generation sequencing (NGS) based 450 genes panel assay. Genomic alterations including single base substitution, short and long insertions/deletions, copy number variations, gene fusions and rearrangement were assessed. Microsatellite stable (MSS) status and TMB were also acquired by NGS algorithms. Results: A total of 340 (8.9%) patients were found to have ARID1A variants. The frequency of ARID1A mutations was 4% in lung adenocarcinoma (N = 74/1833), 8% in squamous cell lung carcinoma (N = 23/278), 12% in colorectal adenocarcinoma (N = 61/530), 11% in hepatocellular carcinoma (N = 52/484), 14% in pancreatic adenocarcinoma (N = 25/177), 15% in gallbladder adenocarcinoma (N = 14/94), 22% in intrahepatic cholangiocarcinoma (N = 47/213), 20% in gastric adenocarcinoma (N = 39/200) and 26% in endometrial adenocarcinoma (N = 5/19). ARID1A variants included truncation (78%), missense/indel (non-frameshift substitution/indel) (16%), splicing site (4%) and rearrangement (2%). Truncation was the most common, recurring in a few hot spots (R1276*, D1850Gfs*4, A339Lfs*24, P224Rfs*8 and Q372Afs*28/Sfs*19). In general, ARID1A mutations correlated with higher TMB (median 17.6 vs 7.4 muts/Mb, P < 0.001) in MSS tumors; especially in lung adenocarcinoma (17 vs 7.5 muts/Mb, P < 0.01), squamous cell lung carcinoma (16.8 vs 11.2 muts/Mb, P < 0.01). TP53 (60%), APC (34%) and KRAS (32%) were the most common co-occurred mutated gene in ARID1A (+) tumors. In more than 20% of ARID1A mutations, PI3K/mTOR pathway genes were altered, such as PIK3CA, PTEN, RNF43 and PIK3R1 genes. Conclusions: Since ARID1A mutations correlate with higher TMB, it could be a potential predictor of response to PD-1/PD-L1 immune checkpoint pathway inhibitors. As reported, ARID1A deficiency promotes mutability and potentiates therapeutic antitumor immunity unleashed by immune checkpoint blockade. Patients harboring ARID1A and PI3K/mTOR pathway mutations may provide useful information for drug discovery and biomarker exploration.

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T-Cell–Inflamed Gene-Expression Profile, Programmed Death Ligand 1 Expression, and Tumor Mutational Burden Predict Efficacy in Patients Treated With Pembrolizumab Across 20 Cancers: KEYNOTE-028

Journal of Clinical Oncology ◽

10.1200/jco.2018.78.2276 ◽

2019 ◽

Vol 37 (4) ◽

pp. 318-327 ◽

Cited By ~ 156

Author(s):

Patrick A. Ott ◽

Yung-Jue Bang ◽

Sarina A. Piha-Paul ◽

Albiruni R. Abdul Razak ◽

Jaafar Bennouna ◽

...

Keyword(s):

Gene Expression ◽

T Cell ◽

Gene Expression Profile ◽

Advanced Solid Tumors ◽

Programmed Death Ligand 1 ◽

Multiple Tumor ◽

Mutational Burden ◽

Programmed Death ◽

Tumor Mutational Burden ◽

Tumor Types

PURPOSE Biomarkers that can predict response to anti–programmed cell death 1 (PD-1) therapy across multiple tumor types include a T-cell–inflamed gene-expression profile (GEP), programmed death ligand 1 (PD-L1) expression, and tumor mutational burden (TMB). Associations between these biomarkers and the clinical efficacy of pembrolizumab were evaluated in a clinical trial that encompassed 20 cohorts of patients with advanced solid tumors. METHODS KEYNOTE-028 ( ClinicalTrials.gov identifier: NCT02054806) is a nonrandomized, phase Ib trial that enrolled 475 patients with PD-L1–positive advanced solid tumors who were treated with pembrolizumab 10 mg/kg every 2 weeks for 2 years or until confirmed disease progression or unacceptable toxicity occurred. The primary end point was objective response rate (ORR; by RECIST v1.1, investigator review). Secondary end points included safety, progression-free survival (PFS), and overall survival (OS). Relationships between T-cell–inflamed GEP, PD-L1 expression, and TMB and antitumor activity were exploratory end points. RESULTS ORRs (with 95% CIs) ranged from 0% (0.0% to 14.2%) in pancreatic cancer to 33% (15.6% to 55.3%) in small-cell lung cancer. Across cohorts, median (95% CI) PFS ranged from 1.7 months (1.5 to 2.9 months) to 6.8 months (1.9 to 14.1 months) in pancreatic and thyroid cancers, respectively, and median OS from 3.9 months (2.8 to 5.5 months) to 21.1 months (9.1 to 22.4 months) in vulvar and carcinoid tumors, respectively. Higher response rates and longer PFS were demonstrated in tumors with higher T-cell–inflamed GEP, PD-L1 expression, and/or TMB. Correlations of TMB with GEP and PD-L1 were low. Response patterns indicate that patients with tumors that had high levels of both TMB and inflammatory markers (GEP or PD-L1) represent a population with the highest likelihood of response. Safety was similar and consistent with prior pembrolizumab reports. CONCLUSION A T-cell–-inflamed GEP, PD-L1 expression, and TMB predicted response to pembrolizumab in multiple tumor types. These biomarkers (alone/in combination) may help identify patients who have a higher likelihood of response to anti–PD-1 therapies across a broad spectrum of cancers.

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Pan-Cancer assessment of tumor mutational burden using a comprehensive genomic profiling assay.

Journal of Clinical Oncology ◽

10.1200/jco.2018.36.5_suppl.157 ◽

2018 ◽

Vol 36 (5_suppl) ◽

pp. 157-157 ◽

Cited By ~ 1

Author(s):

Donna Nichol ◽

Siân Jones ◽

Samuel V. Angiouli ◽

Laurel Keefer ◽

Monica Nesselbush ◽

...

Keyword(s):

Microsatellite Instability ◽

Exome Sequencing ◽

Whole Exome Sequencing ◽

Dynamic Range ◽

Predictive Biomarkers ◽

Clinical Biomarkers ◽

Mutational Burden ◽

Whole Exome ◽

Tumor Mutational Burden ◽

Tumor Types

157 Background: Checkpoint inhibitors (CPIs) have been approved for frontline or subsequent therapies in several indications over the last few years. While patient response can be remarkably durable, many patients do not benefit. Current clinical biomarkers of response to CPIs include microsatellite instability (MSI) and PD-L1 expression. While a proportion of many solid tumors display microsatellite instability, the prevalence is often very low. Similarly, while clinically informative, PD-L1 expression alone is not sufficient to predict therapeutic outcomes with high accuracy. The lack of predictive biomarkers for response highlights the need for improved biomarkers with greater prevalence across tumor types to predict response to CPIs. Multiple clinical studies have revealed that high tumor mutational burden (TMB) is associated with improved clinical response. Methods: Here, we describe the development of a method that can be used to accurately infer mutational burden from a discrete set of targeted regions of interest across the exome. Initially, we performed an assessment of the accuracy across multiple bioinformatics methods for identification of individual sequence mutations (SBS/indels) using orthogonally validated data together with publicly available TCGA whole-exome sequencing data. The targeted regions were then isolated from these datasets to demonstrate analytical performance across several different solid tumor types. Finally, we evaluated independent non-small cell lung cancer (NSCLC) and colorectal carcinoma (CRC) cohorts to demonstrate the analytical accuracy of the assay and bioinformatics approach for determination of mutational burden when compared to whole exome sequencing. Results: In summary, high concordance was observed across a large dynamic range of mutations per megabase of coding sequence. Conclusions: Our data indicate that the assay can be used to accurately determine mutational burden in a range of tumor types, across a spectra of potential mutational burden cut-offs using automated, complex mutation identification algorithms.

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A landscape analysis of immunotherapy-related biomarkers across solid tumors.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.15_suppl.e14268 ◽

2019 ◽

Vol 37 (15_suppl) ◽

pp. e14268-e14268

Author(s):

Lara Ann Kujtan ◽

Scott Morris ◽

Ashiq Masood ◽

Janakiraman Subramanian

Keyword(s):

Solid Tumors ◽

Checkpoint Inhibitor ◽

Predictive Biomarkers ◽

Breast Cancers ◽

High Demand ◽

Lung Cancers ◽

Mutational Burden ◽

Tumor Mutational Burden ◽

Tumor Types ◽

Endometrial Carcinomas

e14268 Background: Checkpoint inhibitor-based immunotherapy has varying success among tumor types and patients. Predictive biomarkers are in high demand to assist with patient selection. Responses to these agents are correlated with programmed cell death ligand 1 (PD-L1) expression, microsatellite instability (MSI), and tumor mutational burden (TMB). Here we evaluated PD-L1 expression, MSI status and TMB in a variety of solid tumors to determine their relationships. Methods: A total of 109 specimens were identified in patients diagnosed with solid tumors that underwent a Paradigm Diagnostic Cancer Test. MSI scores were determined by the number of indels present in runs of 6 homopolymer bases per megabase, with a cut-off of 6 to distinguish between MSI-high (MSI-H) and MSI-stable (MSI-S). TMB scores greater than or equal to 10 muts/Mb were designated as high (TMB-H). Results: Of all tumors, 19.3% were MSI-high. PD-L1 testing was performed in 71.5% of all samples; of these, 21.8% were PD-L1 positive. TMB scores of PD-L1 positive tumors (mean = 10.3 muts/Mb) and PD-L1 negative tumors (mean = 8.6 muts/Mb) did not differ significantly (p = 0.57). All MSI-H tumors were TMB-H, and MSI-H tumors had higher mean TMB scores than MSI-S tumors (57 muts/Mb versus 7.6 muts/Mb; p = 0.06). Among TMB-H tumors, MSI-H status was associated with higher TMB scores compared to MSI-S tumors (55.2 muts/Mb versus 22.1 muts/Mb, p = 0.18). Of the both MSI-S and TMB-H tumors, 68.8% were lung cancers and 18.8% were breast cancers. Tumors both MSI-H and TMB-H were 47.6% gastrointestinal carcinomas and 33.3% endometrial carcinomas. Conclusions: In our analysis, TMB was independent of PD-L1 status. All MSI-H tumors were also TMB-H; these were primarily gastrointestinal and endometrial carcinomas whereas TMB-H tumors that were MSI-S consisted predominantly of lung cancers. This difference may be due to the different mechanisms of acquiring mutations during carcinogenesis in these two tumor types. These data also highlight the need for integrated PD-L1, MSI and TMB testing to identify potential responders to immunotherapy.

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Comparison of tumor mutational burden across eight types of human cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.15_suppl.e15170 ◽

2020 ◽

Vol 38 (15_suppl) ◽

pp. e15170-e15170

Author(s):

Peng Chen ◽

Cuicui Zhang ◽

Zhaoting Meng ◽

Xing Zhang ◽

Minhui Ge ◽

...

Keyword(s):

Colorectal Cancer ◽

Gastric Cancer ◽

Lung Cancer ◽

Pancreatic Cancer ◽

Bile Duct ◽

Liver Cancer ◽

Mutational Burden ◽

Tumor Mutational Burden ◽

Duct Cancer ◽

Tumor Types

e15170 Background: Tumor mutational burden (TMB) is an impressive predictive biomarker for immune checkpoint inhibitors therapy, and immunotherapy is one of the most promising methods for cancer treatment. However, the profile of TMB in various types of cancers was still poorly understood. Methods: In this study, genomic profiling of DNA was performed using next generation sequencing from a 539 genes panel in tumor tissues. The TMB was defined as the numbers of SNVs including synonymous and nonsynonymous mutations, and InDels per megabase in coding regions of sequenced genome. TMB-H was defined as highest mutation load quintile (top 20%) in each cancer type. The values of TMB of 874 patients were compared among eight main tumor types including 174 patients with liver cancer, 32 patients with bile duct cancer, 54 patients with gastric cancer, 119 patients with colorectal cancer, 27 patients with pancreatic cancer, 32 patients with melanoma, 25 patients with glioma and 411 patients with lung cancer cases by multiple independent samples nonparametric Kruskal-Wallis H test via SPSS v22.0. Results: The median values of TMB in liver cancer, bile duct cancer, gastric cancer, colorectal cancer, pancreatic cancer, melanoma, glioma and lung cancer were 10.29, 8.09, 11.03, 10.29, 5.88, 7.35, 5.88 and 7.35 Muts/Mb, respectively. The cut-off values of TMB-H in corresponding eight solid tumors were 16.18, 19.12, 19.85, 16.18, 10.29, 13.24, 10.29 and 18.38 Muts/Mb, respectively. Based on nonparametric Kruskal-Wallis H test, there were significant differences of median TMB values across eight independent tumor types (χ2 = 26.752, p = 3.693×10−4). Significant differences between patients with colorectal cancer and pancreatic cancer ( p = 0.005) or lung cancer ( p = 0.011) were observed via pairwise comparisons. Conclusions: Our study proved the presence of significant differences across eight cancer types, deepened the knowledge of the cancer-specific of TMB, provided useful information in immunology therapy for East Asian patients with solid tumors. As a retrospective study with a relatively small population, the conclusions of this study needed to be verified with a larger sample.

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Clinical sequencing to assess tumor mutational burden as a useful biomarker to immunotherapy in various solid tumors

Therapeutic Advances in Medical Oncology ◽

10.1177/1758835921992992 ◽

2021 ◽

Vol 13 ◽

pp. 175883592199299

Author(s):

Hana Kim ◽

Jung Yong Hong ◽

Jeeyun Lee ◽

Se Hoon Park ◽

Joon Oh Park ◽

...

Keyword(s):

Clinical Practice ◽

Solid Tumors ◽

Solid Tumor ◽

Routine Clinical Practice ◽

High Status ◽

Tumor Patients ◽

Mutational Burden ◽

The Status ◽

Tumor Mutational Burden ◽

Cancer Panel

Background: Immune checkpoint inhibitors (ICIs) have become established as a new therapeutic paradigm in various solid cancers. Predictive biomarkers to ICIs have not yet been fully established. Tumor mutational burden (TMB) has been considered as a useful marker to indicate patients who benefit from ICIs. Methods: We performed next-generation sequencing, including TMB analysis, as a routine clinical practice in 501 patients with advanced gastrointestinal (GI), genitourinary (GU), or rare cancers. The TruSight™ Oncology 500 assay from Illumina was used as a cancer panel. Results: In total, 11.6% (58/501) were identified with tumors with high TMB and MSI-high status was confirmed in seven out of 501 cases (1.4%). High TMB was observed in 11.6% of patients with various solid tumors, including: GU cancers (36.0%, 9/25), colorectal cancer (15.2%, 23/151), biliary tract cancer (14.6%, 7/48), melanoma (14.3%, 3/21), gastric cancer (11.2%, 13/116), hepatocellular carcinoma (8.3%, 1/12), other GI tract cancers (4.5%, 1/22), and sarcoma (1.7%, 1/60). The objective response rate (ORR) to ICIs was 75% (nine out of 12) in solid tumor patients with high TMB and 25% (30 out of 40) in those with non-high TMB. Patients with high TMB had better ORR to ICIs than those with non-high TMB ( p = 0.004). Univariate analysis revealed that the status of PD-L1 expression and of TMB (high versus non-high) had significant association in response to ICIs. However, in multivariate analysis, the status of TMB (high versus non-high) was only significantly related to the response to ICIs ( p = 0.036). Conclusion: In the present study, we analyzed the TMB using a cancer panel for various solid tumor patients in routine clinical practice and also demonstrated the usefulness of TMB to predict the efficacy for ICIs.

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