Blogs

The following articles have been recommended for further reading in the field of cancer immunotherapy by JITC's Guidelines and Consensus Statements Section Editor Dr. Robert L. Ferris.

“Lung tumor–infiltrating _Treg have divergent transcriptional profiles and function linked to checkpoint blockade response” by Dykema et al
Sci Immunol. (2023)

Abstract:
Regulatory T cells (T_reg) are conventionally viewed as suppressors of endogenous and therapy-induced antitumor immunity; however, their role in modulating responses to immune checkpoint blockade (ICB) is unclear. In this study, we integrated single-cell RNA-seq/T cell receptor sequencing (TCRseq) of >73,000 tumor-infiltrating T_reg (TIL-T_reg) from anti–PD-1–treated and treatment-naive non–small cell lung cancers (NSCLC) with single-cell analysis of tumor-associated antigen (TAA)–specific T_reg derived from a murine tumor model. We identified 10 subsets of human TIL-T_reg, most of which have high concordance with murine TIL-T_reg subsets. Only one subset selectively expresses high levels of TNFRSF4 (OX40) and TNFRSF18 (GITR), whose engagement by cognate ligand mediated proliferative programs and NF-κB activation, as well as multiple genes involved in T_reg suppression, including LAG3. Functionally, the OX40^hiGITR^hi subset is the most highly suppressive ex vivo, and its higher representation among total TIL-T_reg correlated with resistance to PD-1 blockade. Unexpectedly, in the murine tumor model, we found that virtually all TIL-T_reg–expressing T cell receptors that are specific for TAA fully develop a distinct T_H1-like signature over a 2-week period after entry into the tumor, down regulating FoxP3 and up-regulating expression of TBX21 (Tbet), IFNG, and certain proinflammatory granzymes. Transfer learning of a gene score from the murine TAA-specific T_H1-like Treg subset to the human single-cell dataset revealed a highly analogous subcluster that was enriched in anti–PD-1 responding tumors. These findings demonstrate that TIL-T_reg partition into multiple distinct transcriptionally defined subsets with potentially opposing effects on ICB-induced antitumor immunity and suggest that TAA-specific TIL-T_reg may positively contribute to antitumor responses.

Why this matters:
This article from Arbor G Dykema et al on TCR sequencing of lung cancer tumor infiltrating lymphocytes, particularly T_reg, provides insight into transcriptional programs of suppressive T cells and tumor antigen specific cells that can be harnessed by effective immune checkpoint blockade, and reflect heterogeneity of immunosuppressive and exhausted TIL.

“Breaking the performance ceiling for neoantigen immunogenicity prediction” by O’Brien et al
Nat Cancer (2023)

Introduction:
Neoantigen-based personalized tumor therapies are emerging as a promising treatment modality. Although efficient and accurate selection of immunogenic neoantigens is a critical determinant of therapy success, the number of candidates to select from frequently exceeds the therapy’s payload. For example, in melanoma there are typically around ten times more candidate mutations than can be included in a neoantigen vaccine. This selection issue is further compounded by a low base rate of neoantigen immunogenicity (~2–6%), which we define here as the ability of a neoantigen to elicit a T cell response, and by the fact that most neoantigens are unique to a tumor. Although in vitro neoantigen immunogenicity screening approaches are improving in accuracy and throughput, they remain resource intensive. Computational immunogenicity-prediction models therefore offer higher efficiency and are frequently relied upon for target selection. Despite recent improvements in models assessing immunogenicity, however, their performance is limited by a shortage of diverse, high-quality data. In particular, the generalizability of models to a highly variable domain, such as neoantigens presented on a diverse set of human leukocyte (HLA) molecules, remains challenging. In this Comment, we focus on approaches for predicting antigen-specific CD8⁺ T cell responses; the prediction of CD4⁺ T cell responses is less well developed, and the issues discussed here are even more pronounced in that context.

Why this matters:
The authors lay out the important hurdles and the shortage of high-quality data and biases in current datasets and predictive models from exome sequencing for epitope prediction, which limit model generalizability. Personalized cancer vaccines require expeditious and accurate prediction to realize the potential of this vaccine strategy.

“Association between pathologic response and survival after neoadjuvant therapy in lung cancer” by Deutsch et al
Nat Med (2023)

Abstract: 
Neoadjuvant immunotherapy plus chemotherapy improves event-free survival (EFS) and pathologic complete response (0% residual viable tumor (RVT) in primary tumor (PT) and lymph nodes (LNs)), and is approved for treatment of resectable lung cancer. Pathologic response assessment after neoadjuvant therapy is the potential analog to radiographic response for advanced disease. However, %RVT thresholds beyond pathologic complete response and major pathologic response (≤10% RVT) have not been explored. Pathologic response was prospectively assessed in the randomized, phase 3 CheckMate 816 trial (NCT02998528), which evaluated neoadjuvant nivolumab (anti-programmed death protein 1) plus chemotherapy in patients with resectable lung cancer. RVT, regression and necrosis were quantified (0–100%) in PT and LNs using a pan-tumor scoring system and tested for association with EFS in a prespecified exploratory analysis. Regardless of LN involvement, EFS improved with 0% versus >0% RVT-PT (hazard ratio = 0.18). RVT-PT predicted EFS for nivolumab plus chemotherapy (area under the curve = 0.74); 2-year EFS rates were 90%, 60%, 57% and 39% for patients with 0–5%, >5–30%, >30–80% and >80% RVT, respectively. Each 1% RVT associated with a 0.017 hazard ratio increase for EFS. Combining pathologic response from PT and LNs helped differentiate outcomes. When compared with radiographic response and circulating tumor DNA clearance, %RVT best approximated EFS. These findings support pathologic response as an emerging survival surrogate. Further assessment of the full spectrum of %RVT in lung cancer and other tumor types is warranted. ClinicalTrials.gov registration: NCT02998528.

Why this matters: 
This article highlights the expanding standard of care neoadjuvant (preoperative) immunotherapy regimens across many solid cancers, and that pathologic response is emerging as a reliable surrogate predictor of survival and clinical benefit.