Abstract 712: Immune checkpoint inhibitor induced tumor gene expression changes in murine syngeneic colon cancer models

552 Background: Colorectal cancer (CRC) incidence and mortality have been rising in the US among adults <55 y. Younger patients with CRC are more likely than older patients to receive postoperative systemic chemotherapy, despite lack of consensus on the prognostic value of age in this disease. CRC diagnosed in younger patients may be biologically different from that in older patients, but characteristics are unknown. Thus, we examined whether age-specific differences were measurable by tumor gene expression using the 12-gene Oncotype DX Colon Recurrence Score (RS) test (Genomic Health, Inc. [GHI]; Redwood City, CA). The Colon RS test is validated to predict risk of recurrence in patients with stage II/III colon cancer. Methods: We analyzed Colon RS test results and single-gene results for the 12 genes by age group (age <40, 40-54, 55-64, and ≥65) using data from the GHI clinical laboratory dated 1/2010 to 7/2017. Results: As of 7/2017, 21,925 Colon RS reports have been delivered. Median age was 63 y; 50% were male. About 23% of patients were <55 y (Table). Mean (SD) RS result was 25 (11). Colon RS result distributions were similar by age group (Table). Expression of individual tumor genes measured in the Colon RS test were also similar by age group (data to be presented). Conclusions: The etiology of the increase in both incidence and mortality from CRC in adults <55 y is poorly understood. Our findings suggest that colon cancer in younger patients is not biologically different from that in older patients, as measured by the Colon RS test in a large cohort referred for testing. As shown by this test in the GHI clinical laboratory experience, most patients with stage II/III colon cancer have low-risk disease, including patients <55 years. Our findings support a biology-driven approach to disease management of patients with stage II/III colon cancer regardless of age. This well-validated genomic assay may identify a group of younger patients for whom adjuvant chemotherapy might represent overtreatment. [Table: see text]

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Gene Expression Profiling in Kidney Transplants with Immune Checkpoint Inhibitor-Associated Adverse Events

Clinical Journal of the American Society of Nephrology ◽

10.2215/cjn.00920121 ◽

2021 ◽

pp. CJN.00920121

Author(s):

Benjamin Adam ◽

Naoka Murakami ◽

Graeme Reid ◽

Katie Du ◽

Ruqaya Jasim ◽

...

Keyword(s):

Gene Expression ◽

T Cell ◽

Interstitial Nephritis ◽

Immune Checkpoint ◽

Immune Checkpoint Inhibitor ◽

Validation Cohort ◽

Checkpoint Inhibitor ◽

Expression Patterns ◽

Acute Interstitial Nephritis ◽

Potential Biomarker

Background and objectives: Immune checkpoint inhibitors are increasingly used to treat various malignancies but their application in kidney transplant patients is complicated by high allograft rejection rates. Immune checkpoint inhibitor-associated rejection is a novel, poorly understood entity demonstrating overlapping histopathological features with immune checkpoint inhibitor-associated acute interstitial nephritis, which poses a challenge for diagnosis and clinical management. We sought to improve the understanding of these entities through biopsy-based gene expression analysis. Design, setting, participants, and measurements: NanoString was used to measure and compare the expression of 725 immune-related genes in 75 archival kidney biopsies, including a 25-sample discovery cohort comprising pure T-cell mediated rejection (TCMR) and immune checkpoint inhibitor-associated acute interstitial nephritis (ICI-AIN), and an independent 50-sample validation cohort comprising ICI-AIN, immune checkpoint inhibitor-associated T-cell mediated rejection (ICI-TCMR), immune checkpoint inhibitor-associated crescentic glomerulonephritis, drug-induced acute interstitial nephritis (Drug-AIN), BK virus nephropathy, and normal biopsies. Results: Significant molecular overlap was observed between ICI-AIN and TCMR. Nevertheless, IFI27, an interferon-alpha induced transcript, was identified and validated as a novel biomarker for differentiating ICI-TCMR from ICI-AIN (validation cohort: P<0.001, AUC=100%, accuracy=86%). Principal component analysis revealed heterogeneity in inflammatory gene expression patterns within sample groups; however, ICI-TCMR and ICI-AIN both demonstrated relatively more molecular overlap with Drug-AIN than TCMR, suggesting potential dominance of hypersensitivity mechanisms in these entities. Conclusions: These results indicate that, although there is significant molecular similarity between immune checkpoint inhibitor-associated rejection and AIN, biopsy-based measurement of IFI27 gene expression represents a potential biomarker for differentiating these entities.

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