Prevalence of prkdc mutations and association with response to immune checkpoint inhibitors in solid tumors.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15250-e15250
Author(s):  
Yi Li ◽  
Chuan-ben Chen ◽  
Yu Chen ◽  
Yan-Fang Guan ◽  
Yingying Huang ◽  
...  
Keyword(s):  
Solid Tumor ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Cox Regression ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarkers ◽  
Predictive Biomarker ◽  
The Cancer Genome Atlas ◽  
Wild Type ◽  
Sequencing Data

e15250 Background: Predictive biomarkers of response to immune checkpoint inhibitors (ICIs) help to identify cancer patients who will benefit from immunotherapy. PRKDC is an important gene relates to DNA double-strand break (DSB) repair and central T-cell tolerance. We aim to investigate the association between PRKDC mutations and tumor mutation burden (TMB), tumor microenvironments (TME), and response to ICIs. Methods: The whole exome sequencing data of 4022 solid tumor samples from the Cancer Genome Atlas (TCGA) and the panel-based sequencing data of 4652 solid tumor samples from GenePlus-Beijing, China were used to analyze TMB. The mRNA expression data of 3541 solid tumor samples from TCGA was used to explore the effect of PRKDC mutation on TME. Four ICIs-treated cohorts were analyzed for verifying the correlation between PRKDC mutation and the response to ICIs. Results: In TCGA datasets and GenePlus datasets, we both found that the TMB in PRKDC mutation samples were significantly higher than PRKDC wild-type samples(P < 0.05, P<0.0001 respectively). When compare to other pivotal DNA damage response (DDR) genes, it showed an identical effect of the degree in TMB by PRKDC mutation with MMR ( PMS2/ MLH1/ MSH2/ MSH6) genes, POLE/D1 and BRCA1/2 mutation (P > 0.05). Further, in TCGA datasets, it showed that PRKDC mutation samples were associated with significant expression increase of CD8+ T cells, NK cells, immune-checkpoint, chemokines etc compared to PRKDC wild-type samples (P < 0.05). In ICIs-treated cohorts, we also found the PRKDC mutation was associated with superior survival(median PFS, not reached (NR) vs. 6.8 months HR, 0.2893 95% CI, 0.1255-0.6672 P = 0.0650, Hellmann cohort; median OS, 1184 days vs. 250 days HR, 0.5126 95% CI, 0.2715-0.9679 P = 0.1020, Allen cohort), and the superiority was significantly in multivariate Cox regression analyses (HR, 0.361 95% CI,0.155-0.841; P = 0.018, Allen cohort; HR, 0.240 95% CI,0.058-0.998; P = 0.050, Hellmann cohort). Conclusions: PRKDC mutations are associated with an increased TMB, an inflamed TME and a better response to ICIs, it may be a potential predictive biomarker for ICIs-immunotherapy.

scholarly journals Current status and future potential of predictive biomarkers for immune checkpoint inhibitors in gastric cancer

ESMO Open ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. e000791 ◽  
Author(s):  
Byung Woog Kang ◽  
Ian Chau
Keyword(s):  
Gastric Cancer ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Gene Expression Signature ◽  
Predictive Biomarkers ◽  
Predictive Biomarker ◽  
Metastatic Gastric Cancer ◽  
Scientific Data ◽  
Current Status

Immunotherapy is revolutionising cancer treatment and has already emerged as standard treatment for patients with recurrent or metastatic gastric cancer (GC). Recent research has been focused on identifying robust predictive biomarkers for GC treated with immune checkpoint inhibitors (ICIs). The expression of programmed cell death protein-ligand-1 (PD-L1) is considered a manifestation of immune response evasion, and several studies have already reported the potential of PD-L1 expression as a predictive parameter for various human malignancies. Meanwhile, based on comprehensive molecular characterisation of GC, testing for Epstein-Barr virus and microsatellite instability is a potential predictive biomarker. Culminating evidence suggests that novel biomarkers, such as the tumour mutational burden and gene expression signature, could indicate the success of treatment with ICIs. However, the exact roles of these biomarkers in GC treated with ICIs remain unclear. Therefore, this study reviews recent scientific data on current and emerging biomarkers for ICIs in GC, which have potential to improve treatment outcomes.

scholarly journals TMB in NSCLC: A Broken Dream?

2021 ◽  
Vol 22 (12) ◽  
pp. 6536
Author(s):  
Sara Bravaccini ◽  
Giuseppe Bronte ◽  
Paola Ulivi
Keyword(s):  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Predictive Power ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarkers ◽  
Predictive Biomarker ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Treatment Paradigm ◽  
Tumor Genome

Although immune checkpoint inhibitors have changed the treatment paradigm of a variety of cancers, including non-small-cell lung cancer, not all patients respond to immunotherapy in the same way. Predictive biomarkers for patient selection are thus needed. Tumor mutation burden (TMB), defined as the total number of somatic/acquired mutations per coding area of a tumor genome (Mut/Mb), has emerged as a potential predictive biomarker of response to immune checkpoint inhibitors. We found that the limited use of TMB in clinical practice is due to the difficulty in its detection and compounded by several different biological, methodological and economic issues. The incorporation of both TMB and PD-L1 expression or other biomarkers into multivariable predictive models could result in greater predictive power.

scholarly journals How to Best Exploit Immunotherapeutics in Advanced Gastric Cancer: Between Biomarkers and Novel Cell-Based Approaches

2021 ◽  
Vol 10 (7) ◽  
pp. 1412
Author(s):  
Michele Ghidini ◽  
Angelica Petrillo ◽  
Andrea Botticelli ◽  
Dario Trapani ◽  
Alessandro Parisi ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Advanced Gastric Cancer ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitor ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarkers ◽  
Clinical Implementation ◽  
T Cell Therapy ◽  
Dismal Prognosis

Despite extensive research efforts, advanced gastric cancer still has a dismal prognosis with conventional treatment options. Immune checkpoint inhibitors have revolutionized the treatment landscape for many solid tumors. Amongst gastric cancer subtypes, tumors with microsatellite instability and Epstein Barr Virus positive tumors provide the strongest rationale for responding to immunotherapy. Various predictive biomarkers such as mismatch repair status, programmed death ligand 1 expression, tumor mutational burden, assessment of tumor infiltrating lymphocytes and circulating biomarkers have been evaluated. However, results have been inconsistent due to different methodologies and thresholds used. Clinical implementation therefore remains a challenge. The role of immune checkpoint inhibitors in gastric cancer is emerging with data from monotherapy in the heavily pre-treated population already available and studies in earlier disease settings with different combinatorial approaches in progress. Immune checkpoint inhibitor combinations with chemotherapy (CT), anti-angiogenics, tyrosine kinase inhibitors, anti-Her2 directed therapy, poly (ADP-ribose) polymerase inhibitors or dual checkpoint inhibitor strategies are being explored. Moreover, novel strategies including vaccines and CAR T cell therapy are also being trialed. Here we provide an update on predictive biomarkers for response to immunotherapy with an overview of their strengths and limitations. We discuss clinical trials that have been reported and trials in progress whilst providing an account of future steps needed to improve outcome in this lethal disease.

RNF43 mutations to predict survival from treatment with immune checkpoint inhibitors and are associated with a high tumor mutation burden in bladder cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e16528-e16528
Author(s):  
Liping Li ◽  
Mengmei Yang ◽  
Mengli Huang
Keyword(s):  
Bladder Cancer ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Negative Regulator ◽  
Wilcoxon Test ◽  
Wild Type ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
The Impact

e16528 Background: Immune checkpoint inhibitors (ICIs) targeting PD-1/L1 have been approved as first-line treatment for cisplatin-ineligible patients and as second-line therapy for patients with metastatic urothelial carcinoma of the bladder. Biomarkers can help select patients who are more likely to response to ICIs. RNF43 is an E3 ubiquitin ligase that acts as a negative regulator of Wnt/β-catenin signaling pathway. In colorectal cancer (CRC) patients treated with immune checkpoint inhibitors (ICIs), RNF43 mutations predicted longer overall survival (OS). The impact of RNF43 mutations on the efficiency of ICIs in bladder cancer(BLC) remains to be explored. Methods: We downloaded the mutation and clinical data of 211 BLC patients treated with ICIs from the immunotherapeutic cohort published by Samstein et al. (2019). OS analyses were conducted using Kaplan-Meier curves and log-rank tests. Wilcoxon test was used for the comparison of TMB. We also downloaded a TCGA cohort for prognostic analysis. The correlations between RNF43 and immune infiltrates were analyzed in the TIMER2.0 database. Statistical significance was set at p = 0.05. Results: RNF43 mutations were identified in 4.3%(9/211) and 3%(13/438) BLC patients in the immunotherapeutic and TCGA cohort, respectively. In the immunotherapeutic cohort, patients with RNF43 mutations had significantly longer OS (25 months vs 8 months; p = 0.015) and higher tumor mutation burden(TMB, 42.3 vs 7.9; p = 3.15E-06) than RNF43-wild-type patients. Different from this, no significant difference was found in OS between RNF43-mutant and RNF43-wild-type BLC patients with standard treatment in the TCGA cohort (p = 0.696). These results indicated that RNF43 was not a prognostic factor but a predictive biomarker of survival in BLC treated with ICIs. No difference was observed in subsets of immune cells between RNF43-mutant and the RNF43-wide-type BLC patients, including neutrophils, macrophages, CD8+ T cells, Tregs, B cells and NK cells. Conclusions: RNF43 mutations may be a predictor of survival benefit from ICIs in bladder cancer and correlated with higher TMB. Further studies in other ICI-treated cohorts are needed to confirm these results.

Genetic ancestry and clinical outcomes to immune checkpoint inhibitors among seven common cancers.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 10536-10536
Author(s):  
Amin Nassar ◽  
Elio Adib ◽  
Sarah Abou Alaiwi ◽  
Elie Akl ◽  
Talal El Zarif ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Clinical Outcomes ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
East Asian ◽  
Genetic Ancestry ◽  
Sequencing Data ◽  
Histologic Subtype ◽  
Cancer Types

10536 Background: Prior studies and clinical trials report associations between self-reported race and clinical outcomes to Immune Checkpoint Inhibitors (ICIs). However, comprehensive studies of ancestry-associated differences in clinical outcomes have not been performed. We derived genetic ancestry scores and assessed clinical outcomes in 1341 patients with cancer treated with ICIs. Methods: Patients at the Dana-Farber Cancer Institute treated with ICIs only and with relevant cancer types and targeted exome sequencing data (Oncopanel) were included. Relevant cancer types included colorectal adenocarcinoma (CRC), esophagogastric adenocarcinoma (EGC), head and neck squamous cell carcinoma (HNSCC), melanoma, non-small cell lung cancer (NSCLC), renal cell carcinoma (RCC), and urothelial carcinoma (UC). We developed a bioinformatics pipeline to infer fine-scale genetic ancestry for each patient (n=1341) directly from tumor sequencing data by leveraging off and on-target sequenced reads and external ancestry reference panels. Three ancestry scores were determined (African, East Asian, European). Overall survival (OS) and time-to-treatment failure (TTF) were compared by Cox logistic regression between ancestral populations. Hazard ratio (HR) was derived using multivariable analysis, adjusted for single versus combination therapy, prior lines of therapy, and tumor mutational burden (TMB, as percentiles). Results: Median follow-up was 37.8 months (m; interquartile range: 35.7-39.5m). Common cancer types included CRC (n=52), EGC (n=114), HNSCC (n=88), melanoma (n=274), NSCLC (n=571), RCC (n=99), and UC (n=143). A higher East Asian ancestry (EAS) was significantly associated with worse OS ( p=0.03) and TTF ( p=0.002) in patients with RCC, independent of the histologic subtype (Table). There was no significant association between any of the three ancestral populations and clinical outcomes in the other 6 cancer types. Conclusions: We described clinical outcomes to ICIs across three global populations in 7 cancers. As the medical field re-evaluates the use of self-reported race in clinical decision-making, we utilize a novel ancestry pipeline that can be readily applied to tumor-only sequencing panels and better characterize non-white populations. We find no ancestry differences in clinical outcomes except in patients with RCC treated with ICIs which will require future validation. We plan to analyze genomic correlates of response by ancestry in each of the cancer types to better understand these diverge clinical behaviors.[Table: see text]

scholarly journals New drug developments in metastatic gastric cancer

2018 ◽  
Vol 11 ◽  
pp. 175628481880807 ◽  
Author(s):  
Aaron C. Tan ◽  
David L. Chan ◽  
Wasek Faisal ◽  
Nick Pavlakis
Keyword(s):  
Gastric Cancer ◽  
Clinical Trials ◽  
Targeted Therapies ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Treatment Options ◽  
Predictive Biomarkers ◽  
Metastatic Gastric Cancer ◽  
New Era

Metastatic gastric cancer is associated with a poor prognosis and novel treatment options are desperately needed. The development of targeted therapies heralded a new era for the management of metastatic gastric cancer, however results from clinical trials of numerous targeted agents have been mixed. The advent of immune checkpoint inhibitors has yielded similar promise and results from early trials are encouraging. This review provides an overview of the systemic treatment options evaluated in metastatic gastric cancer, with a focus on recent evidence from clinical trials for targeted therapies and immune checkpoint inhibitors. The failure to identify appropriate predictive biomarkers has hampered the success of many targeted therapies in gastric cancer, and a deeper understanding of specific molecular subtypes and genomic alterations may allow for more precision in the application of novel therapies. Identifying appropriate biomarkers for patient selection is essential for future clinical trials, for the most effective use of novel agents and in combination approaches to account for growing complexity of treatment options.

scholarly journals Development and validation of blood-based predictive biomarkers for response to PD-(L)-1 checkpoint inhibitors: evidence of a universal systemic core of 3D immunogenetic profiling across multiple oncological indications.

2021 ◽  
Author(s):  
Ewan Hunter ◽  
Mehrnoush Dizfouli ◽  
Christina Koutsothanasi ◽  
Adam Wilson ◽  
Francisco Coroado Santos ◽  
...  
Keyword(s):  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarkers ◽  
Checkpoint Inhibition ◽  
Brain Lymphoma ◽  
3D Genome ◽  
Clinical Assay ◽  
Genomic Approach ◽  
Development And Validation

Unprecedented advantages in cancer treatment with immune checkpoint inhibitors (ICI) remain limited to a subset of patients. Systemic analyses of the regulatory 3D genome architecture linked to individual epigenetics and immunogenetic controls associated with tumour immune evasion mechanisms and immune checkpoint pathways reveals a highly prevalent patient molecular profiles predictive of response to PD-(L)1 immune checkpoint inhibitors. A clinical blood test based on the set of 8 3D genomic biomarkers has been developed and validated on several independent cancer patient cohorts to predict response to PD-(L)1 immune checkpoint inhibition. The predictive 8 biomarker set is derived from prospective observational clinical trials, representing 229 treatments with Pembrolizumab, Atezolizumab, Durvalumab, in diverse indications: melanoma, non-small cell lung, urethral, hepatocellular, bladder, prostate cancer, head and neck, vulvar, colon, breast, bone, brain, lymphoma, larynx cancer, and cervix cancers. The 3D genomic 8 biomarker panel for response to immune checkpoint therapy achieved high accuracy up to 85%, sensitivity of 93% and specificity of 82%. This study demonstrates that a 3D genomic approach could be used to develop a predictive clinical assay for response to PD-(L)1 checkpoint inhibition in cancer patients.

Effect of high-dose corticosteroid use on efficacy of immune checkpoint inhibitors in patients with renal cell carcinoma (RCC).

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 4583-4583
Author(s):  
Chris Labaki ◽  
Sarah Abou Alaiwi ◽  
Andrew Lachlan Schmidt ◽  
Talal El Zarif ◽  
Ziad Bakouny ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Immune Checkpoint ◽  
Renal Cell ◽  
Immune Checkpoint Inhibitors ◽  
Cox Regression ◽  
Checkpoint Inhibitors ◽  
Univariate Analysis ◽  
High Dose ◽  
Line Of Therapy

4583 Background: The use of High-Dose Corticosteroids (HDC) has been linked to poor outcomes in patients with lung cancer treated with immune checkpoint inhibitors (ICIs) (Ricciuti B, JCO, 2019). There is no data on the effect of HDC on renal cell carcinoma patients (RCC) treated with immunotherapy. We hypothesized that HDC use would be associated with worse outcomes in RCC patients receiving ICIs. Methods: This study evaluated a retrospective cohort of patients with RCC at Dana-Farber Cancer Institute in Boston, MA. Clinical information including demographics, IMDC risk score, RCC histology, steroid administration, ICI regimen, line of therapy, time to treatment failure (TTF) and overall survival (OS) were collected. Patients were divided into those receiving HDC (prednisone ≥10 mg or equivalent for ≥ 1 week, HDC group) or not receiving HDC (No-HDC group). HDC administration was evaluated in relation to TTF and OS in a univariate analysis (Log-rank test) and a multivariate analysis (Cox regression). Results: 190 patients with RCC receiving ICIs were included, with a median age of 59 years. HDC were administered to 56 patients and 134 patients received no (N= 116) or only low-dose (N=18) steroids. In the HDC group, 40 patients received steroids for immune-related adverse events, 8 for other cancer-related indications, and 8 for non-oncological indications. There was no difference in TTF between the HDC and No-HDC groups (12-mo TTF rate: 34.8 vs. 32.3%, respectively; log-rank p=0.65). Similarly, there was no difference in OS between the HDC and No-HDC groups (36-mo OS rate: 56.7 vs. 62.4%, respectively; log-rank p=0.97). After adjusting for IMDC risk group, RCC histology, ICI regimen type, and line of therapy, TTF and OS did not differ in the HDC group as compared to No-HDC group (HR=1.14 [95%CI: 0.80-1.62], p=0.44 and HR=1.17 [95%CI: 0.65-2.11], p=0.59, respectively). Conclusions: In this retrospective study of patients with RCC treated with ICIs, administration of high-dose corticosteroids was not associated with worse outcomes.[Table: see text]

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