CTLA-4 blockade and interferon-α induce proinflammatory transcriptional changes in the tumor immune landscape that correlate with pathologic response in melanoma

Abstract

Patients with locally/regionally advanced melanoma were treated with neoadjuvant combination immunotherapy with high-dose interferon α-2b (HDI) and ipilimumab in a phase I clinical trial. Tumor specimens were obtained prior to the initiation of neoadjuvant therapy, at the time of surgery and progression if available. In this study, gene expression profiles of tumor specimens (N = 27) were investigated using the NanoString nCounter® platform to evaluate associations with clinical outcomes (pathologic response, radiologic response, relapse-free survival (RFS), and overall survival (OS)) and define biomarkers associated with tumor response. The Tumor Inflammation Signature (TIS), an 18-gene signature that enriches for response to Programmed cell death protein 1 (PD-1) checkpoint blockade, was also evaluated for association with clinical response and survival. It was observed that neoadjuvant ipilimumab-HDI therapy demonstrated an upregulation of immune-related genes, chemokines, and transcription regulator genes involved in immune cell activation, function, or cell proliferation. Importantly, increased expression of baseline pro-inflammatory genes CCL19, CD3D, CD8A, CD22, LY9, IL12RB1, C1S, C7, AMICA1, TIAM1, TIGIT, THY1 was associated with longer OS (p < 0.05). In addition, multiple genes that encode a component or a regulator of the extracellular matrix such as MMP2 and COL1A2 were identified post-treatment as being associated with longer RFS and OS. In all baseline tissues, high TIS scores were associated with longer OS (p = 0.0166). Also, downregulated expression of cell proliferation-related genes such as CUL1, CCND1 and AAMP at baseline was associated with pathological and radiological response (unadjusted p < 0.01). In conclusion, we identified numerous genes that play roles in multiple biological pathways involved in immune activation, immune suppression and cell proliferation correlating with pathological/radiological responses following neoadjuvant immunotherapy highlighting the complexity of immune responses modulated by immunotherapy. Our observations suggest that TIS may be a useful biomarker for predicting survival outcomes with combination immunotherapy.

Profiling of Tumor Cell‐Delivered Exosome by Surface Enhanced Raman Spectroscopy‐Based Biosensor for Evaluation of Nasopharyngeal Cancer Radioresistance

“…[22] In acute myeloid leukemia and melanoma, patients with higher COL1A2 expression had longer overall survival. [23] In our study, COL1A2 was also down-regulated in radiation-resistant exosomes and was associated with a favorable prognosis in NPC patients, which is in line with the previous evidence that COL1A2 was good prognostic factor. These findings show the promising potential of exosomes as a novel biomarker for the evaluation of NPC radioresistance.…”

Biologically interpretable deep learning to predict response to immunotherapy in advanced melanoma using mutations and copy number variations

“…The other genes including FGFR4, GNAI1, CD36 and FLT1 could alter the tumor microenvironment and further impact ICIs' clinical e cacy, combination their inhibitors and ICIs might be better for melanoma [30][31][32][33]. Khunger et al [34] found that COL1A2 was associated with cancer development and progression, and patients with melanoma were more likely to be bene t from anti-CTLA-4 inhibitors when COL1A2 was highly expressed. Moreover, for the Notch signaling pathway, Cho et al [35]found that it could affect activation of cytotoxic T cells, in ammatory immune microenvironment, in ammatory expression pro le and immunogenicity, and Li et al [36] reported that patients with nonsmall cell lung cancer (NSCLC) treated by ICIs could own longer survival time if they had high-mutated Notch signaling.…”

Identification of the SHREK Family of Proteins as Broad-Spectrum Host Antiviral Factors

“…Previous studies have shown that several of the SHREK proteins, such as PSGL-1 [ 5 ], CD43 [ 37 ], CD164 [ 34 , 38 ], TMEM123 [ 39 ], MUC1 [ 40 ], and MUC4 [ 41 ], are induced by interferons. However, SHREK proteins in general are likely different from interferon-induced restriction factors, and can be constitutively expressed in specific cell populations.…”