A PD-1 /PD-L1 proximity assay as a theranostic marker for PD-1 blockade in patients with metastatic melanoma

Extensive-stage small-cell lung cancer in patients receiving atezolizumab plus carboplatin-etoposide: stratification of outcome based on a composite score that combines gene expression profiling and immune characterization of microenvironment

PURPOSE

Small-cell lung cancer (SCLC) is an aggressive disease with a dismal prognosis. The addition of immune checkpoints inhibitors to standard platinum-based chemotherapy in first-line setting achieves a durable benefit only in a patient subgroup. Thus, the identification of predictive biomarkers is an urgent unmet medical need.

EXPERIMENTAL DESIGN

Tumor samples from naive extensive-stage (ES) SCLC patients receiving atezolizumab plus carboplatin-etoposide were analyzed by gene expression profiling and two 9-color multiplex immunofluorescence panels, to characterize the immune infiltrate and SCLC subtypes. Associations of tissue biomarkers with time-to-treatment failure (TTF), progression-free survival (PFS) and overall survival (OS), were assessed.

RESULTS

42 patients were included. Higher expression of exhausted CD8-related genes was independently associated with a longer TTF and PFS while increased density of B lymphocytes correlated with longer TTF and OS. Higher percentage of M2-like macrophages close to tumor cells and of CD8+T cells close to CD4+T lymphocytes correlated with increased risk of TF and longer survival, respectively. A lower risk of TF, disease progression and death was associated with a higher density of ASCL1+tumor cells while the expression of POU2F3 correlated with a shorter survival. A composite score combining the expression of exhausted CD8-related genes, B lymphocyte density, ASCL1 tumor expression and quantification of CD163+macrophages close to tumor cells, was able to stratify patients into high-risk and low-risk groups.

CONCLUSIONS

In conclusion, we identified tissue biomarkers and a combined score that can predict a higher benefit from chemoimmunotherapy in ES-SCLC patients.

Analysis of the clinical efficacy and safety of anti-PD-1 immune checkpoint inhibitors in locally advanced nasopharyngeal cancer

OBJECTIVE

To analyze the efficacy and adverse effects of anti-PD-1 immune checkpoint inhibitors aimed at nasopharyngeal carcinoma (NPC).

METHODS

During the first stage of the study, using 40 patients with stage III/IVa NPC treated with anti-PD-1 immune checkpoint inhibitors in combination with chemoradiotherapy as a first-line treatment (observation group) and 70 patients with NPC treated with chemoradiotherapy alone (control group). In the second stage of the study, 88 patients with NPC treated with immune checkpoint inhibitors were grouped according to the number of lines of immunotherapy, the number of times, and the types of application.

RESULTS

Observation of the short-term effects in the first stage indicated that the objective response rate (ORR) of the observation group and the control group against primary foci of NPC was 75.0% versus 40.0%; the mortality rate of the observation group was much lower than that of the control group. The overall first-line treatment evaluation of the observation vs. control groups were as follows: ORR (67.5% vs. 38.6%); median PFS (17.52 vs. 17.21 months); and median OS (18.68 vs. 18.14 months), respectively (p < 0.05). The second stage of the study had an ORR of 53.4%, and the efficacy of immunotherapy was related to staging, timing, and frequency.

CONCLUSION

Anti-PD-1 immune checkpoint inhibitors combined with chemoradiotherapy as the first-line treatment for nasopharyngeal carcinoma may improve patient outcomes significantly. Timing, frequency, and the type of immunotherapy exerted an effect on the efficacy of immunotherapy. Adverse effects that occurred during treatment were tolerable and controllable.

Immune Marker Spatial Distribution and Clinical Outcome after PD-1 Blockade in Mismatch Repair-deficient, Advanced Colorectal Carcinomas

PURPOSE

Targeting the programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PD-L1) interaction has led to durable responses in fewer than half of patients with mismatch repair-deficient (MMR-d) advanced colorectal cancers. Immune contexture, including spatial distribution of immune cells in the tumor microenvironment (TME), may predict immunotherapy outcome.

EXPERIMENTAL DESIGN

Immune contexture and spatial distribution, including cell-to-cell distance measurements, were analyzed by multiplex immunofluorescence (mIF) in primary colorectal cancers with d-MMR (N = 33) from patients treated with anti-PD-1 antibodies. By digital image analysis, density, ratio, intensity, and spatial distribution of PD-L1, PD-1, CD8, CD3, CD68, LAG3, TGFβR2, MHC-I, CD14, B2M, and pan-cytokeratin were computed. Feature selection was performed by regularized Cox regression with LASSO, and a proportional hazards model was fitted to predict progression-free survival (PFS).

RESULTS

For predicting survival among patients with MMR-d advanced colorectal cancer receiving PD-1 blockade, cell-to-cell distance measurements, but not cell densities or ratios, achieved statistical significance univariately. By multivariable feature selection, only mean number of PD-1+ cells within 10 μm of a PD-L1+ cell was significantly predictive of PFS. Dichotomization of this variable revealed that those with high versus low values had significantly prolonged PFS [median not reached (>83 months) vs. 8.5 months (95% confidence interval (95% CI), 4.7-NR)] with a median PFS of 28.4 months for all patients [adjusted HR (HRadj) = 0.14; 95% CI, 0.04-0.56; P = 0.005]. Expression of PD-1 was observed on CD8+ T cells; PD-L1 on CD3+ and CD8+ T lymphocytes, macrophages (CD68+), and tumor cells.

CONCLUSIONS

In d-MMR colorectal cancers, PD-1+ to PD-L1+ receptor to ligand proximity is a potential predictive biomarker for the effectiveness of PD-1 blockade.

Deciphering transcriptomic determinants of the divergent link between PD-L1 and immunotherapy efficacy

Programmed cell death ligand 1 (PD-L1) expression remains the most widely used biomarker for predicting response to immune checkpoint inhibitors (ICI), but its predictiveness varies considerably. Identification of factors accounting for the varying PD-L1 performance is urgently needed. Here, using data from three independent trials comprising 1239 patients, we have identified subsets of cancer with distinct PD-L1 predictiveness based on tumor transcriptome. In the Predictiveness-High (PH) group, PD-L1+ tumors show better overall survival, progression-free survival, and objective response rate with ICI than PD-L1- tumors across three trials. However, the Predictiveness-Low (PL) group demonstrates an opposite trend towards better outcomes for PD-L1- tumors. PD-L1+ tumors from the PH group demonstrate the superiority of ICI over chemotherapy, whereas PD-L1+ tumors from the PL group show comparable efficacy between two treatments or exhibit an opposite trend favoring chemotherapy. This observation of context-dependent predictiveness remains strong regardless of immune subtype (Immune-Enriched or Non-Immune), PD-L1 regulation mechanism (adaptative or constitutive), tumor mutation burden, or neoantigen load. This work illuminates avenues for optimizing the use of PD-L1 expression in clinical decision-making and trial design, although this exploratory concept should be further confirmed in large trials.

Cured or Not? Long-term Outcomes of Immunotherapy Responders. Focus on Melanoma

PURPOSE OF REVIEW

Immune checkpoint inhibitors (ICIs) demonstrated robust antitumor activity and tolerable safety in advanced melanoma. Data on long-term outcome of patients who benefited from this therapy and who are still free of progression despite ICI discontinuation is now available. We review here the characteristics of long-term ICI responders and address the critical question of cure.

RECENT FINDINGS

Long-term outcome of patients with metastatic melanoma enrolled in large phase 2 and phase 3 clinical trials evaluating ICI in metastatic melanoma is now available. Durable responses, with more than 6 years of median follow-up, may persist after discontinuation. They occur more frequently in patients who achieved a complete response rather than in patients who had partial response or stable disease. Although long-term clinical benefit is more frequent in patients with high PDL-1 expression and smaller tumor burden, durable response may also be observed regardless of baseline characteristics. In patients with asymptomatic brain metastasis, combined immunotherapy (ipilimumab plus nivolumab) may also lead to long-term remission. Clinical trials confirm the durable antitumor activity of ICI. Although the hope for cure seems reasonable for many patients in this situation, late relapses may occur and no relapse-predictive biomarkers have been identified yet. Long-term responders who relapse can respond to a rechallenge of ICI although data are limited concerning the rate and the duration of this new response.

PD-L1 methylation restricts PD-L1/PD-1 interactions to control cancer immune surveillance

Immune checkpoint inhibitors targeting programmed cell death protein 1 (PD-1) or programmed cell death 1 ligand 1 (PD-L1) have enabled some patients with cancer to experience durable, complete treatment responses; however, reliable anti-PD-(L)1 treatment response biomarkers are lacking. Our research found that PD-L1 K162 was methylated by SETD7 and demethylated by LSD2. Furthermore, PD-L1 K162 methylation controlled the PD-1/PD-L1 interaction and obviously enhanced the suppression of T cell activity controlling cancer immune surveillance. We demonstrated that PD-L1 hypermethylation was the key mechanism for anti-PD-L1 therapy resistance, investigated that PD-L1 K162 methylation was a negative predictive marker for anti-PD-1 treatment in patients with non-small cell lung cancer, and showed that the PD-L1 K162 methylation:PD-L1 ratio was a more accurate biomarker for predicting anti-PD-(L)1 therapy sensitivity. These findings provide insights into the regulation of the PD-1/PD-L1 pathway, identify a modification of this critical immune checkpoint, and highlight a predictive biomarker of the response to PD-1/PD-L1 blockade therapy.

Identification and validation of pyroptosis-related gene landscape in prognosis and immunotherapy of ovarian cancer

BACKGROUND

Emerging evidence has highlighted the biological significance of pyroptosis in tumor tumorigenesis and progression. Nonetheless, the potential roles of pyroptosis in tumor immune microenvironment and target therapy of ovarian cancer (OC) remain unknown.

METHODS

In this study, with a series of bioinformatic and machine learning approaches, we comprehensively evaluated genetic alterations and transcriptome profiles of pyroptosis-associated genes (PYAGs) with TCGA-OV datasets. Consensus molecular clustering was performed to determine pyroptosis-associated clusters (PACs) and gene clusters in OC. Subsequently, component analysis algorithm (PCA) was employed to construct Pyrsig score and a highly accurate nomogram was established to evaluate its efficacy. Meanwhile, we systematically performed association analysis for these groups with prognosis, clinical features, TME cell-infiltrating characteristics, drug response and immunotherapeutic efficacy. Immunohistochemistry was conducted to verify molecular expression with clinical samples.

RESULTS

The somatic mutations and copy number variation (CNV) of 51 PYRGs in OC samples were clarified. Two distinct PACs (PAC1/2) and three gene clusters (A/B/C) were identified based on 1332 OC samples, PAC1 and gene cluster A were significantly associated with favorable overall survival (OS), clinicopathological features and TME cell-infiltrating characteristics. Subsequently, Pyrsig score was successfully established to demonstrate the prognostic value and immune characteristics of pyroptosis in OC, low Pyrsig score, characterized by activated immune cell infiltration, indicated prolonged OS, increased sensitivity of some chemotherapeutic drugs and enhanced efficacy of anti-PD-L1 immunotherapy, Consequently, a nomogram was successfully established to improve the clinical applicability and stability of Pyrsig score. With clinical OC samples, GSDMD and GZMB proteins were validated highly expressed in OC and associated with immune infiltration and Pyrsig score, GZMB and CD8 proteins were regarded as independent prognostic factors of OC.

CONCLUSION

This work revealed pyroptosis played a non-negligible role in prognosis value, clinicopathological characteristics and tumor immune infiltration microenvironment in OC, which provided novel insights into identifying and characterizing landscape of tumor immune microenvironment, thereby guiding more effective prognostic evaluation and tailored immunotherapy strategies of OC.