Translating the evolving molecular landscape of tumors to biomarkers of response for cancer immunotherapy

Impact of metabolic and nutritional disorders on the synergy between radiotherapy and immunotherapy in non-small-cell lung cancer

BACKGROUND

Patient conditions including metabolic and nutritional status were reported to be prognostic or predictive biomarkers of anti-cancer treatment, while little attention has been paid to its association with the synergistic effect of radiotherapy (RT) and immune checkpoint inhibitors (ICIs).

METHODS

Metastatic non-small-cell lung cancer (mNSCLC) patients who received concurrent RT and ICIs between 2018 and 2023 were included in this study. In addition, mNSCLC patients treated with ICIs alone were enrolled to confirm the synergetic effect of RT and ICIs. Clinicopathological, metabolic and nutritional factors were collected to analyze their influence on progression-free survival (PFS), overall survival and abscopal control time. Abdominal CT was used to obtain body composition data including abdominal obesity and muscle mass.

RESULTS

A total of 96 mNSCLC patients who received RT concurrent with ICIs were included, and a synergistic effect of significantly improved PFS was observed when compared with patients treated with ICIs alone. Among patients undergoing concurrent RT and ICIs, both total adipose area(HR = 2.81,P = 0.029) and prognosis nutritional index (HR = 0.24, P<0.001) were confirmed as independent positive prognostic markers for PFS. Later-line of immunotherapy (HR = 3.67, P = 0.006), low visceral-to-subcutaneous ratio (VSR, HR = 5.53, P = 0.002), high total adipose area (HR = 5.21, P = 0.0016) and high prognostic nutritional index (HR = 0.24, P = 0.002) were independent risk factors for abscopal progression. Then, we established a scoring system consisting of metabolic and nutritional factors to stratify patients into three groups. Patients with non-visceral obesity and good nutrition status have the longest PFS and abscopal control survival, while patients with poor nutritional status regardless of body composition represent the worst prognosis.

CONCLUSION

Metabolic and nutritional status, particularly the combined assessment of body composition and nutritional index, serves as a valuable predictor for the synergistic efficacy of concurrent RT and ICIs.

Click Chemistry-Assisted Rejuvenation of Aging T Cells Sensitizes Aged Mice to Tumor Immunotherapy

Enormous resources have been devoted to address the suboptimal response of tumor patients to immunotherapy. However, a crucial yet often overlooked factor in these effects is the strong correlation between the occurrence and development of tumors and the immune dysfunction associated with aging. Our study aims to rejuvenate aging T cells within tumor-draining lymph nodes (TdLNs) by using targeted delivery of rapamycin, a macrolide capable of mitigating aging-related decline in immune function, thereby enhancing the antitumor efficacy of immunotherapy in aged mice. The targeted delivery system relies on a bioorthogonal reaction that harnesses the click chemistry between the azide (N3) groups artificially introduced onto TdLNs and the dibenzocyclooctyne (DBCO) groups attached to the rapamycin-loaded micelles administered intradermally. Experimental data demonstrate that this approach has effectively restored the functionality of impaired CD8+ T cells in aged mice, thereby enhancing the antitumor response to immune checkpoint blockade (ICB) therapy to levels comparable to those in young mice. This study presents a promising strategy to combat the resistance to immunotherapeutic approaches commonly encountered among elderly tumor patients.

Discovery of a DNA repair-associated radiosensitivity index for predicting radiotherapy efficacy in breast cancer

Purpose

Radiotherapy is a cornerstone of breast cancer (BRCA) treatment. Accurately predicting tumor radiosensitivity is critical for optimizing therapeutic outcomes and personalizing treatment strategies. DNA repair pathways are key determinants of radiotherapy response. Thus, we aimed to develop a novel DNA repair-related radiosensitivity model and to identify potential targets for enhancing radiotherapy efficacy.

Methods

A retrospective study was conducted using data from 942 BRCA patients from TCGA database. A radiosensitivity model, comprising a radiosensitivity index, was developed using LASSO regression analysis. Patients were stratified into radiosensitive (RS) and radioresistant (RR) groups based on their radiosensitivity index (RSI). Associations between the RSI, clinicopathological parameters, and PD-L1 status were analyzed. The CIBERSORT and ESTIMATE algorithms were employed to characterize the immune landscape of the tumor microenvironment. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm and pRRophetic platform were used to predict treatment responses. Key genes identified in the radiosensitivity model were further validated using in vitro qRT-PCR experiments.

Results

We successfully constructed a radiosensitivity index incorporating 10 DNA repair-related genes. Patients in the RS group exhibited significantly better prognosis compared to the RR group, but this benefit was limited to those receiving radiotherapy. This survival benefit associated with the radiosensitivity signature was absent in patients who did not receive radiotherapy. The RS group displayed a distinct molecular profile characterized by enrichment of TGF-β signaling and protein secretion pathways, potentially contributing to enhanced radiosensitivity. Furthermore, the RS group exhibited increased infiltration of immune cells. Notably, the RS-PD-L1-high subgroup demonstrated the most favorable survival outcomes and highest immune cell infiltration, highlighting their potential responsiveness to immunotherapy. In addition, the RR group exhibited a distinct profile characterized by enrichment of DNA repair pathways and a heightened sensitivity to CDK and HER2 inhibitors. Conversely, this group displayed resistance to DNA-damaging drugs. These findings were supported by in vitro experiments using MCF-7 and radioresistant MCF-7/IR cell lines, confirming differential expression of key radiosensitivity index genes.

Conclusion

In conclusion, we established a radiosensitivity model for predicting radiotherapy benefit in breast cancer. Our study reveals a strong association between radiosensitivity, enhanced antitumor immunity, and potential immunotherapy benefit, particularly within the RS-PD-L1-high subgroup.

Overview on biomarkers for immune oncology drugs

Although immune checkpoint inhibitors (ICIs) are widely used in clinical oncology, less than half of treated cancer patients derive benefit from this therapy. Both tumor- and host-related variables are implicated in response to ICIs. The predictive value of PD-L1 expression is confined only to several cancer types, so this molecule is not an agnostic biomarker. Highly elevated tumor mutation burden (TMB) caused either by excessive carcinogenic exposure or by a deficiency in DNA repair is a reliable indicator for ICI efficacy, as exemplified by tumors with high-level microsatellite instability (MSI-H). Other potentially relevant tumor-related characteristics include gene expression signatures, pattern of tumor infiltration by immune cells, and, perhaps, some immune-response modifying somatic mutations. Host-related factors have not yet been comprehensively considered in relevant clinical trials. Microbiome composition, markers of systemic inflammation [e.g., neutrophil-to-lymphocyte ratio (NLR)], and human leucocyte antigen (HLA) diversity may influence the efficacy of ICIs. Studies on ICI biomarkers are likely to reveal modifiable tumor or host characteristics, which can be utilized to direct the antitumor immune defense. Examples of the latter approach include tumor priming to immune therapy by cytotoxic drugs and elevation of ICI efficacy by microbiome modification.

Advancing precision cancer immunotherapy drug development, administration, and response prediction with AI-enabled Raman spectroscopy

Molecular characterization of tumors is essential to identify predictive biomarkers that inform treatment decisions and improve precision immunotherapy development and administration. However, challenges such as the heterogeneity of tumors and patient responses, limited efficacy of current biomarkers, and the predominant reliance on single-omics data, have hindered advances in accurately predicting treatment outcomes. Standard therapy generally applies a "one size fits all" approach, which not only provides ineffective or limited responses, but also an increased risk of off-target toxicities and acceleration of resistance mechanisms or adverse effects. As the development of emerging multi- and spatial-omics platforms continues to evolve, an effective tumor assessment platform providing utility in a clinical setting should i) enable high-throughput and robust screening in a variety of biological matrices, ii) provide in-depth information resolved with single to subcellular precision, and iii) improve accessibility in economical point-of-care settings. In this perspective, we explore the application of label-free Raman spectroscopy as a tumor profiling tool for precision immunotherapy. We examine how Raman spectroscopy's non-invasive, label-free approach can deepen our understanding of intricate inter- and intra-cellular interactions within the tumor-immune microenvironment. Furthermore, we discuss the analytical advances in Raman spectroscopy, highlighting its evolution to be utilized as a single "Raman-omics" approach. Lastly, we highlight the translational potential of Raman for its integration in clinical practice for safe and precise patient-centric immunotherapy.

Local Exosome Inhibition Potentiates Mild Photothermal Immunotherapy Against Breast Cancer

Limited immune infiltration within the tumor microenvironment (TME) hampers the efficacy of immune checkpoint blockade (ICB) therapy. To enhance immune infiltration, mild photothermal therapy (PTT) is often combined with immunotherapy. However, the impact of mild PTT on the TME remains unclear. The bioinformatics analyses reveal that mild PTT amplifies immune cell infiltration and stimulates T-cell activity. Notably, it accelerates the release of tumor cell-derived exosomes (TEX) and upregulates PD-L1 expression on both tumor cells and TEX. Consequently, it is proposed that locally inhibiting TEX release is crucial for overcoming the adverse effects of mild PTT, thereby enhancing ICB therapy. Thus, a multi-stage drug delivery system is designed that concurrently delivers photosensitizers (reduced graphene oxide nanosheets, NRGO), anti-PD-L1 antibodies, and exosome inhibitors (sulfisoxazole). The system employs a temperature-sensitive lipid gel as the primary carrier, with NRGO serving as a secondary carrier that supports photothermal conversion and incorporation of sulfisoxazole. Importantly, controlled drug release is achieved using near-infrared radiation. The findings indicate that this local combination therapy remodels the immunosuppressive TME through exosome inhibition and enhanced immune cell infiltration, while also boosting T-cell activity to trigger systemic antitumor immunity, showcasing the remarkable efficacy of this combination strategy in eradicating cold tumors.

Quantitative peripheral live single T-cell dynamic polyfunctionality profiling predicts lung cancer checkpoint immunotherapy treatment response and clinical outcomes

Background

Predictive biomarkers for immune checkpoint inhibitors (ICIs), e.g., programmed death ligand-1 (PD-L1) tumor proportional score (TPS), remain limited in clinical applications. Predictive biomarkers that require invasive tumor biopsy procedures are practically challenging especially when longitudinal follow-up is required. Clinical utility of tissue-based PD-L1 TPS also becomes diluted when ICI is combined with chemotherapies. Peripheral single T-cell dynamic polyfunctionality profiling offers the opportunity to reveal rare T-cell subpopulations that are polyfunctional and responsible for the underlying ICI treatment molecular response that bulk biological assays cannot achieve. Here, we evaluated a novel live single-cell functional liquid biopsy cytokine profiling platform, IsoLight, as a potential predictive biomarker to track ICI treatment response and clinical outcomes in non-small cell lung cancer (NSCLC).

Methods

Peripheral blood mononuclear cell samples of 10 healthy donors and 10 NSCLC patients undergoing ICI-based therapies were collected longitudinally pre-/post-ICI treatment after ≥2 cycles under institutional review board (IRB)-approved protocols. Cancer blood samples were collected from unresectable advanced stage (III-IV) NSCLC patients. Clinical course and treatment response and survival outcomes were extracted from electronic health records, with treatment response assessed by treating oncologists based on RECIST. CD4+ and CD8+ T-cells were enriched magnetically and analyzed on the IsoLight platform. Single T-cells were captured in microchambers on IsoCode chips for proteomic immune cytokines profiling. Functional polyfunctionality data from 55,775 single cells were analyzed with IsoSpeak software, 2D- and 3D-t-distributed stochastic neighbor embedding (t-SNE) analysis, kappa coefficient, and Kaplan-Meier survival plots. P values ≤0.05 is considered statistically significant.

Results

Pre-treatment baseline polyfunctionality profiles could not differentiate NSCLC patients from healthy subjects, and could not differentiate ICI responders from non-responders. We found a statistically significant difference between responders and non-responders in CD8+ T-cells' changes in overall polyfunctionality (ΔPolyFx) (P=0.01) and polyfunctional strength index (ΔPSI) (P=0.006) in our dynamic pre-/post-treatment single cell measurements, both performing better than PD-L1 TPS alone (P=0.08). In the 3D-t-SNE analysis, subpopulations of post-treatment CD8+ T-cells in ICI responders displayed distinct immune cytokine profiles from those in pre-treatment cells. CD8+ T-cells ΔPolyFx and ΔPSI scores performed better than PD-L1 TPS in ICI response correlation. Moreover, combined PD-L1 strong TPS and ΔPSI >15 scores strongly correlated with early ICI response with a robust kappa coefficient of 1.0 (P=0.003), which was previously statistically established to indicate a perfect agreement between the prediction and actual response status. Interestingly, high CD4+ T-cells ΔPSI >5 was found to correlate with a strong trend of improved progression-free survival (3.9-fold) (10.8 vs. 2.8 months; P=0.07) and overall survival (3-fold) (34.5 vs. 11.5 months; P=0.09) in ICI-treated patients.

Conclusions

Our study nominates single peripheral T-cell polyfunctionality dynamics analysis to be a promising liquid biopsy platform to determine potential ICI predictive biomarker in NSCLC. It warrants further studies in larger prospective cohorts to validate the clinical utilities and to further optimize cancer immunotherapy.

Noninvasive early identification of durable clinical benefit from immune checkpoint inhibition: a prospective multicenter study (NCT04566432)

Immune checkpoint inhibitors (ICIs) have changed the treatment landscape for patients with non-small cell lung cancer (NSCLC). In spite of durable responses in some patients, many patients develop early disease progression during the ICI treatment. Thus, early identification of patients with no durable benefit would facilitate the clinical decision for these patients. In this prospective, multicenter study, 101 non-EGFR/ALK patients who received ICI treatment were enrolled after screening 328 stage III-IV NSCLC patients. At the date of cutoff, 83 patients were eligible for ICI efficacy evaluation, with 56 patients having progress-free survival (PFS) over 6 months, which was defined as durable clinical benefit (DCB). A multimodal model was established by integrating normalized bTMB, early dynamic of ctDNA and the first RECIST response. This model could robustly predict DCB with area under the curve (AUC) of 0.878, sensitivity of 79.2% at 86.4% specificity (accuracy = 80.0%). This model was further validated in the independent cohort of the DIREct-On study with AUC of 0.887, sensitivity of 94.7% at 85.3% specificity (accuracy = 90.3%). Patients with higher predict scores had substantially longer PFS than those with lower scores (training cohort: median PFS 13.6 vs 4.2 months, P < 0.001, HR = 0.24; validation cohort: median PFS 11.0 vs 2.2 months, P < 0.001, HR = 0.17). Taken together, these results demonstrate that integrating early changes of ctDNA, normalized bTMB, and the first RECIST response can provide accurate, noninvasive, and early prediction of durable benefits for NSCLC patients treated with ICIs. Further prospective studies are warranted to validate these findings and guide clinical decision-making for optimal immunotherapy in NSCLC patients.

Novel Spatial Approaches to Dissect the Lung Cancer Immune Microenvironment

Lung cancer is a deadly disease with the highest rates of mortality. Over recent decades, a better understanding of the biological mechanisms implicated in its pathogenesis has led to the development of targeted therapies and immunotherapy, resulting in improvements in patient outcomes. To better understand lung cancer tumor biology and advance towards precision oncology, a comprehensive tumor profile is necessary. In recent years, novel in situ spatial multiomics approaches have emerged offering a more detailed view of the spatial location of tumor and tumor microenvironment cells, identifying their unique composition and functional status. In this sense, novel multiomics platforms have been developed to evaluate tumor heterogeneity, gene expression, metabolic reprogramming, signaling pathway activation, cell-cell interactions, and immune cell programs. In lung cancer research, several studies have used these spatial technologies to locate cells and associated them with histological features that are relevant to the pathogenesis of lung adenocarcinoma. These advancements may unveil further molecular and immune mechanisms in tumor biology that will lead to the discovery of biomarkers for treatment prediction and prognosis. In this review, we provide an overview of more widely used and emerging pathology-based approaches for spatial immune profiling in lung cancer and how they enhance our understanding of tumor biology and immune response.

Clinical Outcomes and Histologic Findings of Patients With Hepatocellular Carcinoma With Durable Partial Response or Durable Stable Disease After Receiving Atezolizumab Plus Bevacizumab

PURPOSE

Durable partial response (PR) and durable stable disease (SD) are often seen in patients with hepatocellular carcinoma (HCC) receiving atezolizumab plus bevacizumab (atezo-bev). This study investigates the outcome of these patients and the histopathology of the residual tumors.

PATIENTS AND METHODS

The IMbrave150 study's atezo-bev group was analyzed. PR or SD per RECIST v1.1 lasting more than 6 months was defined as durable. For histologic analysis, a comparable real-world group of patients from Japan and Taiwan who had undergone resection of residual tumors after atezo-bev was investigated.

RESULTS

In the IMbrave150 study, 56 (77.8%) of the 72 PRs and 41 (28.5%) of the 144 SDs were considered durable. The median overall survival was not estimable for patients with durable PR and 23.7 months for those with durable SD. The median progression-free survival was 23.2 months for patients with durable PR and 13.2 months for those with durable SD. In the real-world setting, a total of 38 tumors were resected from 32 patients (23 PRs and nine SDs) receiving atezo-bev. Pathologic complete responses (PCRs) were more frequent in PR tumors than SD tumors (57.7% v 16.7%, P = .034). PCR rate correlated with time from atezo-bev initiation to resection and was 55.6% (5 of 9) for PR tumors resected beyond 8 months after starting atezo-bev, a time practically corresponding to the durable PR definition used for IMbrave150. We found no reliable radiologic features to predict PCR of the residual tumors.

CONCLUSION

Durable PR patients from the atezo-bev group showed a favorable outcome, which may be partly explained by the high rate of PCR lesions. Early recognition of PCR lesions may help subsequent treatment decision.

Cancer Biomarkers and Precision Oncology: A Review of Recent Trends and Innovations

The discovery of cancer-specific biomarkers has resulted in major advancements in the field of cancer diagnostics and therapeutics, therefore significantly lowering cancer-related morbidity and mortality. Cancer biomarkers can be generally classified as prognostic biomarkers that predict specific disease outcomes and predictive biomarkers that predict disease response to targeted therapeutic interventions. As research in the area of predictive biomarkers continues to grow, precision medicine becomes far more integrated in cancer treatment. This article presents a general overview on the most recent advancements in the area of cancer biomarkers, immunotherapy, artificial intelligence, and pharmacogenomics of the Middle East.

Opportunities and challenges of using circulating tumor DNA to predict lung cancer immunotherapy efficacy

Immune checkpoint inhibitors (ICIs), particularly anti-programmed death 1 (PD-1)/ programmed death ligand 1 (PD-L1) antibodies, have led to significant progress in lung cancer treatment. However, only a minority of patients have responses to these therapies. Detecting peripheral blood of circulating tumor DNA (ctDNA) allows minimally invasive diagnosis, characterization, and monitoring of lung cancer. ctDNA has potential to be a prognostic biomarker and a predictor of the response to ICI therapy since it can indicate the genomic status and tumor burden. Recent studies on lung cancer have shown that pretreatment ctDNA analysis can detect residual proliferative disease in the adjuvant immunotherapy setting and evaluate tumor burden in patients with metastatic disease. Early ctDNA dynamics can not only predict the clinical outcome of ICI therapy but also help distinguish between pseudoprogression and real progression. Furthermore, in addition to quantitative assessment, ctDNA can also detect genetic predictors of response to ICI therapy. However, barriers still exist in the application of ctDNA analysis in clinical lung cancer treatment. The predictive value of ctDNA in lung cancer immunotherapy requires further identification and resolution of these challenges. This review aims to summarize the existing data of ctDNA analysis in patients receiving immunotherapy for lung cancer, understand the limitations of clinical treatment, and discuss future research directions.

A Review of Immunotherapy for Head and Neck Cancer

The introduction of immune checkpoint inhibitors (ICIs) to oncological care has transformed the management of various malignancies, including head and neck squamous cell carcinoma (HNSCC), offering improved outcomes. The first-line treatment of recurrent and malignant HNSCC for many years was combined platinum, 5-fluorouracil, and cetuximab. Recently, the ICI pembrolizumab was approved as a first-line treatment, with or without chemotherapy, based on tumor and immune cell percentage of programmed-death ligand 1 (PD-L1). Multiple head and neck (HN) cancer trials have subsequently explored immunotherapies in combination with surgery, chemotherapy, and/or radiation. Immunotherapy regimens may be personalized by tumor biomarker, including PD-L1 content, tumor mutational burden, and microsatellite instability. However, further clinical trials are needed to refine biomarker-driven protocols and standardize pathological methods to guide combined regimen timing, sequencing, and deescalation. Gaps remain for protocols using immunotherapy to reverse oral premalignant lesions, particularly high-risk leukoplakias. A phase II nonrandomized controlled trial, using the ICI nivolumab, showed a 2-y cancer-free survival of 73%, although larger trials are needed. Guidelines are also needed to standardize the role of dental evaluation and care before, during, and after immunotherapy, specifically in regard to oral immune-related adverse events and their impact on cancer recurrence. Standardized diagnostic and oral care coordination strategies to close these gaps are needed to ensure continued success of HN cancer immunotherapy.

Tumour mutational burden: clinical utility, challenges and emerging improvements

Tumour mutational burden (TMB), defined as the total number of somatic non-synonymous mutations present within the cancer genome, varies across and within cancer types. A first wave of retrospective and prospective research identified TMB as a predictive biomarker of response to immune-checkpoint inhibitors and culminated in the disease-agnostic approval of pembrolizumab for patients with TMB-high tumours based on data from the Keynote-158 trial. Although the applicability of outcomes from this trial to all cancer types and the optimal thresholds for TMB are yet to be ascertained, research into TMB is advancing along three principal avenues: enhancement of TMB assessments through rigorous quality control measures within the laboratory process, including the mitigation of confounding factors such as limited panel scope and low tumour purity; refinement of the traditional TMB framework through the incorporation of innovative concepts such as clonal, persistent or HLA-corrected TMB, tumour neoantigen load and mutational signatures; and integration of TMB with established and emerging biomarkers such as PD-L1 expression, microsatellite instability, immune gene expression profiles and the tumour immune contexture. Given its pivotal functions in both the pathogenesis of cancer and the ability of the immune system to recognize tumours, a profound comprehension of the foundational principles and the continued evolution of TMB are of paramount relevance for the field of oncology.

ImmunoPET imaging of LAG-3 expression in tumor microenvironment with 68Ga-labelled cyclic peptides tracers: from bench to bedside

BACKGROUND

Lymphocyte activation gene 3 (LAG-3) has been considered as the next generation of immune checkpoint and a promising prognostic biomarker of immunotherapy. As with programmed cell death protein-1/programmed death-ligand 1 and cytotoxic T-lymphocyte antigen-4 inhibitors, positron emission tomography (PET) imaging strategies could benefit the development of clinical decision-making of LAG-3-related therapy. In this study, we developed and validated 68Ga-labeled cyclic peptides tracers for PET imaging of LAG-3 expression in bench-to-bedside studies.

METHODS

A series of LAG-3-targeted cyclic peptides were modified and radiolabeled with 68GaCl3 and evaluated their affinity and specificity, biodistribution, pharmacokinetics, and radiation dosimetry in vitro and in vivo. Furthermore, hu-PBL-SCID (PBL) mice models were constructed to validate the capacity of [68Ga]Ga-CC09-1 for mapping of LAG-3+ lymphocytes infiltrates using longitudinal PET imaging. Lastly, [68Ga]Ga-CC09-1 was translated into the first-in-human studies to assess its safety, biodistribution and potential for imaging of LAG-3 expression.

RESULTS

A series of cyclic peptides targeting LAG-3 were employed as lead compounds to design and develop 68Ga-labeled PET tracers. In vitro binding assays showed higher affinity and specificity of [68Ga]Ga-CC09-1 in Chinese hamster ovary-human LAG-3 cells and peripheral blood mononuclear cells. In vivo PET imaging demonstrated better imaging capacity of [68Ga]Ga-CC09-1 with a higher tumor uptake of 1.35±0.33 per cent injected dose per gram and tumor-to-muscle ratio of 17.18±3.20 at 60 min post-injection. Furthermore, [68Ga]Ga-CC09-1 could detect the LAG-3+ lymphocyte infiltrates in spleen, lung and salivary gland of PBL mice. In patients with melanoma and non-small cell lung cancer, primary lesions with modest tumor uptake were observed in [68Ga]Ga-CC09-1 PET, as compared with that of [18F]FDG PET. More importantly, [68Ga]Ga-CC09-1 delineated the heterogeneity of LAG-3 expression within large tumors.

CONCLUSION

These findings consolidated that [68Ga]Ga-CC09-1 is a promising PET tracer for quantifying the LAG-3 expression in tumor microenvironment, indicating its potential as a companion diagnostic for patients stratification and therapeutic response monitoring in anti-LAG-3 therapy.

A muti-modal feature fusion method based on deep learning for predicting immunotherapy response

Immune checkpoint therapy (ICT) has greatly improved the survival of cancer patients in the past few years, but only a small number of patients respond to ICT. To predict ICT response, we developed a multi-modal feature fusion model based on deep learning (MFMDL). This model utilizes graph neural networks to map gene-gene relationships in gene networks to low dimensional vector spaces, and then fuses biological pathway features and immune cell infiltration features to make robust predictions of ICT. We used five datasets to validate the predictive performance of the MFMDL. These five datasets span multiple types of cancer, including melanoma, lung cancer, and gastric cancer. We found that the prediction performance of multi-modal feature fusion model based on deep learning is superior to other traditional ICT biomarkers, such as ICT targets or tumor microenvironment-associated markers. In addition, we also conducted ablation experiments to demonstrate the necessity of fusing different modal features, which can improve the prediction accuracy of the model.

Precision Immuno-Oncology in NSCLC through Gender Equity Lenses

Precision immuno-oncology involves the development of personalized cancer treatments that are influenced by the unique nature of an individual's DNA, immune cells, and their tumor's molecular characterization. Biological sex influences immunity; females typically mount stronger innate and adaptive immune responses than males. Though more research is warranted, we continue to observe an enhanced benefit for females with lung cancer when treated with combination chemoimmunotherapy in contrast to the preferred approach of utilizing immunotherapy alone in men. Despite the observed sex differences in response to treatments, women remain underrepresented in oncology clinical trials, largely as a result of gender-biased misconceptions. Such exclusion has resulted in the development of less efficacious treatment guidelines and clinical recommendations and has created a knowledge gap in regard to immunotherapy-related survivorship issues such as fertility. To develop a more precise approach to care and overcome the exclusion of women from clinical trials, flexible trial schedules, multilingual communication strategies, financial, and transportation assistance for participants should be adopted. The impact of intersectionality and other determinants of health that affect the diagnosis, treatment, and outcomes in women must also be considered in order to develop a comprehensive understanding of the unique impact of immunotherapy in all women with lung cancer.

Thermophoretic glycan profiling of extracellular vesicles for triple-negative breast cancer management

Triple-negative breast cancer (TNBC) is a highly metastatic and heterogeneous type of breast cancer with poor outcomes. Precise, non-invasive methods for diagnosis, monitoring and prognosis of TNBC are particularly challenging due to a paucity of TNBC biomarkers. Glycans on extracellular vesicles (EVs) hold the promise as valuable biomarkers, but conventional methods for glycan analysis are not feasible in clinical practice. Here, we report that a lectin-based thermophoretic assay (EVLET) streamlines vibrating membrane filtration (VMF) and thermophoretic amplification, allowing for rapid, sensitive, selective and cost-effective EV glycan profiling in TNBC plasma. A pilot cohort study shows that the EV glycan signature reaches 91% accuracy for TNBC detection and 96% accuracy for longitudinal monitoring of TNBC therapeutic response. Moreover, we demonstrate the potential of EV glycan signature for predicting TNBC progression. Our EVLET system lays the foundation for non-invasive cancer management by EV glycans.

Gut microbes as medical signature for the effectiveness of immunotherapy in patients with advanced non-small cell lung cancer

Lung cancer (LC) is the most common cause of cancer-related death worldwide and poses a severe threat to public health. Immunotherapy with checkpoint blockers has improved the outlook for advanced non-small cell lung cancer (NSCLC) therapy. For the treatment of patients with advanced NSCLC, antibodies such as anti-programmed death 1 (anti-PD1), anti-programmed death ligand 1 (anti-PD-L1), and anti-cytotoxic T lymphocyte-associated antigen 4 (anti-CTLA-4) are of paramount importance. Anti-PD-1 and anti-PD-L1 monoclonal antibody therapies are used to block the PD-1/PD-L1 pathway and identify cancerous cells to the body's defenses. Antibodies directed against CTLA-4 (anti-CTLA-4) have also been shown to improve survival rates in patients with NSCLC. Currently, other immunotherapy approaches like neoadjuvant immune checkpoint inhibitors (NAICIs) and chimeric antigen receptor T-cell (CAR-T) therapies are applied in NSCLC patients. NAICIs are used for resectable and early stage NSCLC and CAR-T is used to find more useful epitope sites for lung tumors and destroy cancer cells. A patient's gut microbiota might influence how their immune system reacts to NSCLC immunotherapy. The majority of intestinal microbes stimulate helper/cytotoxic T cells, induce natural killer (NK) cells, activate various toll-like receptors (TLR), build up cluster of differentiation 8 (CD8), increase PD-1 production, and attract chemokine receptors towards cancer cells. Thus, they serve as immune inducers in NSCLC immunotherapy. Nonetheless, certain bacteria can function as immune suppressors by inhibiting DC proliferation, stopping CD28 trafficking, restoring CD80/CD86, increasing immunological tolerance, and upsetting Th17 cells. Therefore, they are prevalent in non-responders with NSCLC immunotherapy.

Genetic insights into carbohydrate sulfotransferase 8 and its impact on the immunotherapy efficacy of cancer

Immune checkpoint blockade (ICB) is a promising therapy for solid tumors, but its effectiveness depends on biomarkers that are not precise. Here, we utilized genome-wide association study to investigate the association between genetic variants and tumor mutation burden to interpret ICB response. We identified 16 variants (p < 5 × 10-8) probed to 17 genes on 9 chromosomes. Subsequent analysis of one of the most significant loci in 19q13.11 suggested that the rs111308825 locus at the enhancer is causal, as its A allele impairs KLF2 binding, leading to lower carbohydrate sulfotransferase 8 (CHST8) expression. Breast cancer cells expressing CHST8 suppress T cell activation, and Chst8 loss attenuates tumor growth in a syngeneic mouse model. Further investigation revealed that programmed death-ligand 1 (PD-L1) and its homologs could be sulfated by CHST8, resulting in M2-like macrophage enrichment in the tumor microenvironment. Finally, we confirmed that low-CHST8 tumors have better ICB response, supporting the genetic effect and clinical value of rs111308825 for ICB efficacy prediction.

Elucidating the Heterogeneity of Immunotherapy Response and Immune-Related Toxicities by Longitudinal ctDNA and Immune Cell Compartment Tracking in Lung Cancer

PURPOSE

Although immunotherapy is the mainstay of therapy for advanced non-small cell lung cancer (NSCLC), robust biomarkers of clinical response are lacking. The heterogeneity of clinical responses together with the limited value of radiographic response assessments to timely and accurately predict therapeutic effect-especially in the setting of stable disease-calls for the development of molecularly informed real-time minimally invasive approaches. In addition to capturing tumor regression, liquid biopsies may be informative in capturing immune-related adverse events (irAE).

EXPERIMENTAL DESIGN

We investigated longitudinal changes in circulating tumor DNA (ctDNA) in patients with metastatic NSCLC who received immunotherapy-based regimens. Using ctDNA targeted error-correction sequencing together with matched sequencing of white blood cells and tumor tissue, we tracked serial changes in cell-free tumor load (cfTL) and determined molecular response. Peripheral T-cell repertoire dynamics were serially assessed and evaluated together with plasma protein expression profiles.

RESULTS

Molecular response, defined as complete clearance of cfTL, was significantly associated with progression-free (log-rank P = 0.0003) and overall survival (log-rank P = 0.01) and was particularly informative in capturing differential survival outcomes among patients with radiographically stable disease. For patients who developed irAEs, on-treatment peripheral blood T-cell repertoire reshaping, assessed by significant T-cell receptor (TCR) clonotypic expansions and regressions, was identified on average 5 months prior to clinical diagnosis of an irAE.

CONCLUSIONS

Molecular responses assist with the interpretation of heterogeneous clinical responses, especially for patients with stable disease. Our complementary assessment of the peripheral tumor and immune compartments provides an approach for monitoring of clinical benefits and irAEs during immunotherapy.

Plasma cell-free DNA as a sensitive biomarker for multi-cancer detection and immunotherapy outcomes prediction

BACKGROUND

Cell-free DNA (cfDNA) has shown promise in detecting various cancers, but the diagnostic performance of cfDNA end motifs for multiple cancer types requires verification. This study aimed to assess the utility of cfDNA end motifs for multi-cancer detection.

METHODS

This study included 206 participants: 106 individuals with cancer, representing 20 cancer types, and 100 healthy individuals. The participants were divided into training and testing cohorts. All plasma cfDNA samples were profiled by whole-genome sequencing. A random forest model was constructed using cfDNA 4 bp-end-motif profiles to predict cancer in the training cohort, and its performance was evaluated in the testing cohort. Additionally, a separate random forest model was developed to predict immunotherapy responses.

RESULTS

In the training cohort, the model based on 4 bp-end-motif profiles achieved an AUC of 0.962 (95% CI 0.936-0.987). The AUC in the testing cohort was 0.983 (95% CI 0.960-1.000). The model also maintained excellent predictive ability in different tumor sub-cohorts, including lung cancer (AUC 0.918, 95% CI 0.862-0.974), gastrointestinal cancer (AUC 0.966, 95% CI 0.938-0.993), and other cancer cohort (AUC 0.859, 95% CI 0.776-0.942). Moreover, the model utilizing 4 bp-end-motif profiles exhibited sensitivity in identifying responders to immunotherapy (AUC 0.784, 95% CI 0.609-0.960).

CONCLUSION

The model based on 4 bp-end-motif profiles demonstrates superior sensitivity in multi-cancer detection. Detection of 4 bp-end-motif profiles may serve as potential predictive biomarkers for cancer immunotherapy.

Immunotherapy of Multiple Myeloma: Current Status as Prologue to the Future

The landscape of therapeutic measures to treat multiple myeloma has undergone a seismic shift since the dawn of the current century. This has been driven largely by the introduction of new classes of small molecules, such as proteasome blockers (e.g., bortezomib) and immunomodulators (e.g., lenalidomide), as well as by immunotherapeutic agents starting with the anti-CD38 monoclonal antibody daratumumab in 2015. Recently, other immunotherapies have been added to the armamentarium of drugs available to fight this malignancy. These include the bispecifics teclistamab, talquetamab, and elranatamab, and the chimeric antigen receptor (CAR) T-cell products idecabtagene vicleucel (ide-cel) and ciltacabtagene autoleucel (cilta-cel). While the accumulated benefits of these newer agents have resulted in a more than doubling of the disease's five-year survival rate to nearly 60% and improved quality of life, the disease remains incurable, as patients become refractory to the drugs and experience relapse. This review covers the current scope of antimyeloma immunotherapeutic agents, both those in clinical use and in development. Included in the discussion are additional monoclonal antibodies (mAbs), antibody-drug conjugates (ADCs), bi- and multitargeted mAbs, and CAR T-cells and emerging natural killer (NK) cells, including products intended for "off-the-shelf" (allogeneic) applications. Emphasis is placed on the benefits of each along with the challenges that need to be surmounted if MM is to be cured.

ctDNA response after pembrolizumab in non-small cell lung cancer: phase 2 adaptive trial results

Circulating tumor DNA (ctDNA) has shown promise in capturing primary resistance to immunotherapy. BR.36 is a multi-center, randomized, ctDNA-directed, phase 2 trial of molecular response-adaptive immuno-chemotherapy for patients with lung cancer. In the first of two independent stages, 50 patients with advanced non-small cell lung cancer received pembrolizumab as standard of care. The primary objectives of stage 1 were to ascertain ctDNA response and determine optimal timing and concordance with radiologic Response Evaluation Criteria in Solid Tumors (RECIST) response. Secondary endpoints included the evaluation of time to ctDNA response and correlation with progression-free and overall survival. Maximal mutant allele fraction clearance at the third cycle of pembrolizumab signified molecular response (mR). The trial met its primary endpoint, with a sensitivity of ctDNA response for RECIST response of 82% (90% confidence interval (CI): 52-97%) and a specificity of 75% (90% CI: 56.5-88.5%). Median time to ctDNA response was 2.1 months (90% CI: 1.5-2.6), and patients with mR attained longer progression-free survival (5.03 months versus 2.6 months) and overall survival (not reached versus 7.23 months). These findings are incorporated into the ctDNA-driven interventional molecular response-adaptive second stage of the BR.36 trial in which patients at risk of progression are randomized to treatment intensification or continuation of therapy. ClinicalTrials.gov ID: NCT04093167 .

hMENA isoforms regulate cancer intrinsic type I IFN signaling and extrinsic mechanisms of resistance to immune checkpoint blockade in NSCLC

BACKGROUND

Understanding how cancer signaling pathways promote an immunosuppressive program which sustains acquired or primary resistance to immune checkpoint blockade (ICB) is a crucial step in improving immunotherapy efficacy. Among the pathways that can affect ICB response is the interferon (IFN) pathway that may be both detrimental and beneficial. The immune sensor retinoic acid-inducible gene I (RIG-I) induces IFN activation and secretion and is activated by actin cytoskeleton disturbance. The actin cytoskeleton regulatory protein hMENA, along with its isoforms, is a key signaling hub in different solid tumors, and recently its role as a regulator of transcription of genes encoding immunomodulatory secretory proteins has been proposed. When hMENA is expressed in tumor cells with low levels of the epithelial specific hMENA11a isoform, identifies non-small cell lung cancer (NSCLC) patients with poor prognosis. Aim was to identify cancer intrinsic and extrinsic pathways regulated by hMENA11a downregulation as determinants of ICB response in NSCLC. Here, we present a potential novel mechanism of ICB resistance driven by hMENA11a downregulation.

METHODS

Effects of hMENA11a downregulation were tested by RNA-Seq, ATAC-Seq, flow cytometry and biochemical assays. ICB-treated patient tumor tissues were profiled by Nanostring IO 360 Panel enriched with hMENA custom probes. OAK and POPLAR datasets were used to validate our discovery cohort.

RESULTS

Transcriptomic and biochemical analyses demonstrated that the depletion of hMENA11a induces IFN pathway activation, the production of different inflammatory mediators including IFNβ via RIG-I, sustains the increase of tumor PD-L1 levels and activates a paracrine loop between tumor cells and a unique macrophage subset favoring an epithelial-mesenchymal transition (EMT). Notably, when we translated our results in a clinical setting of NSCLC ICB-treated patients, transcriptomic analysis revealed that low expression of hMENA11a, high expression of IFN target genes and high macrophage score identify patients resistant to ICB therapy.

CONCLUSIONS

Collectively, these data establish a new function for the actin cytoskeleton regulator hMENA11a in modulating cancer cell intrinsic type I IFN signaling and extrinsic mechanisms that promote protumoral macrophages and favor EMT. These data highlight the role of actin cytoskeleton disturbance in activating immune suppressive pathways that may be involved in resistance to ICB in NSCLC.

Elucidating the heterogeneity of immunotherapy response and immune-related toxicities by longitudinal ctDNA and immune cell compartment tracking in lung cancer

Purpose

Although immunotherapy is the mainstay of therapy for advanced non-small cell lung cancer (NSCLC), robust biomarkers of clinical response are lacking. The heterogeneity of clinical responses together with the limited value of radiographic response assessments to timely and accurately predict therapeutic effect -especially in the setting of stable disease-call for the development of molecularly-informed real-time minimally invasive predictive biomarkers. In addition to capturing tumor regression, liquid biopsies may be informative in evaluating immune-related adverse events (irAEs).

Experimental design

We investigated longitudinal changes in circulating tumor DNA (ctDNA) in patients with metastatic NSCLC who received immunotherapy-based regimens. Using ctDNA targeted error-correction sequencing together with matched sequencing of white blood cells and tumor tissue, we tracked serial changes in cell-free tumor load (cfTL) and determined molecular response for each patient. Peripheral T-cell repertoire dynamics were serially assessed and evaluated together with plasma protein expression profiles.

Results

Molecular response, defined as complete clearance of cfTL, was significantly associated with progression-free (log-rank p=0.0003) and overall survival (log-rank p=0.01) and was particularly informative in capturing differential survival outcomes among patients with radiographically stable disease. For patients who developed irAEs, peripheral blood T-cell repertoire reshaping, assessed by significant TCR clonotypic expansions and regressions were noted on-treatment.

Conclusions

Molecular responses assist with interpretation of heterogeneous clinical responses especially for patients with stable disease. Our complementary assessment of the tumor and immune compartments by liquid biopsies provides an approach for monitoring of clinical benefit and immune-related toxicities for patients with NSCLC receiving immunotherapy.

Statement of translational relevance

Longitudinal dynamic changes in cell-free tumor load and reshaping of the peripheral T-cell repertoire capture clinical outcomes and immune-related toxicities during immunotherapy for patients with non-small cell lung cancer.

Gallium-68-labeled Peptide PET Quantifies Tumor Exposure of PD-L1 Therapeutics

PURPOSE

Immune checkpoint therapy (ICT) is currently ineffective in a majority of patients. Tumor drug exposure measurements can provide vital insights into mechanisms involved in the resistance of solid tumors to those therapeutics; however, tools to quantify in situ drug exposure are few. We have investigated the potential of programmed death-ligand 1 (PD-L1) pharmacodynamics, quantified using PET, to inform on the tumor exposure of anti-PD-L1 (aPD-L1) therapeutics.

EXPERIMENTAL DESIGN

To noninvasively quantify PD-L1 levels, we first developed a novel peptide-based gallium-68-labeled binder, [68Ga]Ga-DK223, and evaluated its in vivo distribution, pharmacokinetics, and PD-L1 specificity in preclinical models of triple-negative breast cancer and urothelial carcinoma with variable PD-L1 expression. We then quantified baseline and accessible PD-L1 levels in tumors as a noninvasive pharmacodynamic measure to assess tumor exposure to two aPD-L1 antibodies (avelumab and durvalumab).

RESULTS

DK223 exhibited a KD of 1.01±0.83 nmol/L for PD-L1 and inhibited the PD-1:PD-L1 interaction in a dose-dependent manner. [68Ga]Ga-DK223 provides high-contrast PET images within 60 minutes of administration and detects PD-L1 in an expression-dependent manner in xenograft models. PD-L1 pharmacodynamics measured using [68Ga]Ga-DK223-PET revealed that avelumab and durvalumab had similar exposure early during therapy, but only durvalumab exhibited sustained exposure at the tumor.

CONCLUSIONS

[68Ga]Ga-DK223 detected variable PD-L1 levels and exhibited salient features required for clinical translation. [68Ga]Ga-DK223-PET could be useful for quantifying total PD-L1 levels at baseline and accessible PD-L1 levels during therapy to understand drug exposure at the tumor, thus supporting its use for guiding and optimizing ICT.

Advances in artificial intelligence to predict cancer immunotherapy efficacy

Tumor immunotherapy, particularly the use of immune checkpoint inhibitors, has yielded impressive clinical benefits. Therefore, it is critical to accurately screen individuals for immunotherapy sensitivity and forecast its efficacy. With the application of artificial intelligence (AI) in the medical field in recent years, an increasing number of studies have indicated that the efficacy of immunotherapy can be better anticipated with the help of AI technology to reach precision medicine. This article focuses on the current prediction models based on information from histopathological slides, imaging-omics, genomics, and proteomics, and reviews their research progress and applications. Furthermore, we also discuss the existing challenges encountered by AI in the field of immunotherapy, as well as the future directions that need to be improved, to provide a point of reference for the early implementation of AI-assisted diagnosis and treatment systems in the future.

Liquid biopsy approaches to capture tumor evolution and clinical outcomes during cancer immunotherapy

Circulating cell-free tumor DNA (ctDNA) can serve as a real-time biomarker of tumor burden and provide unique insights into the evolving molecular landscape of cancers under the selective pressure of immunotherapy. Tracking the landscape of genomic alterations detected in ctDNA may reveal the clonal architecture of the metastatic cascade and thus improve our understanding of the molecular wiring of therapeutic responses. While liquid biopsies may provide a rapid and accurate evaluation of tumor burden dynamics during immunotherapy, the complexity of antitumor immune responses is not fully captured through single-feature ctDNA analyses. This underscores a need for integrative studies modeling the tumor and the immune compartment to understand the kinetics of tumor clearance in association with the quality of antitumor immune responses. Clinical applications of ctDNA testing in patients treated with immune checkpoint inhibitors have shown both predictive and prognostic value through the detection of genomic biomarkers, such as tumor mutational burden and microsatellite instability, as well as allowing for real-time monitoring of circulating tumor burden and the assessment of early on-therapy responses. These efforts highlight the emerging role of liquid biopsies in selecting patients for cancer immunotherapy, monitoring therapeutic efficacy, determining the optimal duration of treatment and ultimately guiding treatment selection and sequencing. The clinical translation of liquid biopsies is propelled by the increasing number of ctDNA-directed interventional clinical trials in the immuno-oncology space, signifying a critical step towards implementation of liquid biopsies in precision immuno-oncology.