Existing and Emerging Biomarkers for Immune Checkpoint Immunotherapy in Solid Tumors

Enhancing Tumor Immunotherapy by Multivalent Anti-PD-L1 Nanobody Assembled via Ferritin Nanocage

Increasing immunotherapy response rate and durability can lead to significant improvements in cancer care. To address this challenge, a novel multivalent immune checkpoint therapeutic platform is constructed through site-specific ligation of anti-PD-L1 nanobody (Nb) on ferritin (Ftn) nanocage. Nb-Ftn blocks PD-1/PD-L1 interaction and downregulates PD-L1 levels via endocytosis-induced degradation. In addition, the cage structure of Ftn allows encapsulation of indocyanine green (ICG), an FDA-approved dye. Photothermal treatment with Nb-Ftn@ICG induces immunogenic death of tumor cells, which improves systemic immune response via maturation of dendritic cells and enhanced infiltration of T cells. Moreover, Nb-Ftn encapsulation significantly enhances cellular uptake, tumor accumulation and retention of ICG. In vivo assays showed that this nanoplatform ablates the primary tumor, suppresses abscopal tumors and inhibits tumor metastasis, leading to a prolonged survival rate. This work presents a novel strategy for improving cancer immunotherapy using multivalent nanobody-ferritin conjugates as immunological targeting and enhancing carriers.

Prediction of immunotherapy responsiveness in melanoma through single-cell sequencing-based characterization of the tumor immune microenvironment

Immune checkpoint inhibitors (ICB) therapy have emerged as effective treatments for melanomas. However, the response of melanoma patients to ICB has been highly heterogenous. Here, by analyzing integrated scRNA-seq datasets from melanoma patients, we revealed significant differences in the TiME composition between ICB-resistant and responsive tissues, with resistant or responsive tissues characterized by an abundance of myeloid cells and CD8+ T cells or CD4+ T cell predominance, respectively. Among CD4+ T cells, CD4+ CXCL13+ Tfh-like cells were associated with an immunosuppressive phenotype linked to immune escape-related genes and negative regulation of T cell activation. We also develop an immunotherapy response prediction model based on the composition of the immune compartment. Our predictive model was validated using CIBERSORTx on bulk RNA-seq datasets from melanoma patients pre- and post-ICB treatment and showed a better performance than other existing models. Our study presents an effective immunotherapy response prediction model with potential for further translation, as well as underscores the critical role of the TiME in influencing the response of melanomas to immunotherapy.

The use of pembrolizumab monotherapy for the management of head and neck squamous cell carcinoma (HNSCC) in the UK

Pembrolizumab has received approval in the UK as first-line monotherapy for recurrent and/or metastatic HNSCC (R/M HNSCC) following the results of the KEYNOTE-048 trial, which demonstrated a longer overall survival (OS) in comparison to the EXTREME chemotherapy regimen in patients with a combined positive score (CPS) ≥1. In this article, we provide retrospective real-world data on the role of pembrolizumab monotherapy as first-line systemic therapy for HNSCC across 18 centers in the UK from March 20, 2020 to May 31, 2021. 211 patients were included, and in the efficacy analysis, the objective response rate (ORR) was 24.7%, the median progression-free survival (PFS) was 4.8 months (95% confidence interval [CI]: 3.6-6.1), and the median OS was 10.8 months (95% CI 9.0-12.5). Pembrolizumab monotherapy was well tolerated, with 18 patients having to stop treatment owing to immune-related adverse events (irAEs). 53 patients proceeded to second-line treatment with a median PFS2 of 10.2 months (95% CI: 8.8-11.5). Moreover, patients with documented irAEs had a statistically significant longer median PFS (11.3 vs. 3.3 months; log-rank p value = <.001) and median OS (18.8 vs. 8.9 months; log-rank p value <.001). The efficacy and safety of pembrolizumab first-line monotherapy for HNSCC has been validated using real-world data.

Epigenetic MLH1 silencing concurs with mismatch repair deficiency in sporadic, naturally occurring colorectal cancer in rhesus macaques

BACKGROUND

Naturally occurring colorectal cancers (CRC) in rhesus macaques share many features with their human counterparts and are useful models for cancer immunotherapy; but mechanistic data are lacking regarding the comparative molecular pathogenesis of these cancers.

METHODS

We conducted state-of-the-art imaging including CT and PET, clinical assessments, and pathological review of 24 rhesus macaques with naturally occurring CRC. Additionally, we molecularly characterized these tumors utilizing immunohistochemistry (IHC), microsatellite instability assays, DNAseq, transcriptomics, and developed a DNA methylation-specific qPCR assay for MLH1, CACNA1G, CDKN2A, CRABP1, and NEUROG1, human markers for CpG island methylator phenotype (CIMP). We furthermore employed Monte-Carlo simulations to in-silico model alterations in DNA topology in transcription-factor binding site-rich promoter regions upon experimentally demonstrated DNA methylation.

RESULTS

Similar cancer histology, progression patterns, and co-morbidities could be observed in rhesus as reported for human CRC patients. IHC identified loss of MLH1 and PMS2 in all cases, with functional microsatellite instability. DNA sequencing revealed the close genetic relatedness to human CRCs, including a similar mutational signature, chromosomal instability, and functionally-relevant mutations affecting KRAS (G12D), TP53 (R175H, R273*), APC, AMER1, ALK, and ARID1A. Interestingly, MLH1 mutations were rarely identified on a somatic or germline level. Transcriptomics not only corroborated the similarities of rhesus and human CRCs, but also demonstrated the significant downregulation of MLH1 but not MSH2, MSH6, or PMS2 in rhesus CRCs. Methylation-specific qPCR suggested CIMP-positivity in 9/16 rhesus CRCs, but all 16/16 exhibited significant MLH1 promoter hypermethylation. DNA hypermethylation was modelled to affect DNA topology, particularly propeller twist and roll profiles. Modelling the DNA topology of a transcription factor binding motif (TFAP2A) in the MLH1 promoter that overlapped with a methylation-specific probe, we observed significant differences in DNA topology upon experimentally shown DNA methylation. This suggests a role of transcription factor binding interference in epigenetic silencing of MLH1 in rhesus CRCs.

CONCLUSIONS

These data indicate that epigenetic silencing suppresses MLH1 transcription, induces the loss of MLH1 protein, abrogates mismatch repair, and drives genomic instability in naturally occurring CRC in rhesus macaques. We consider this spontaneous, uninduced CRC in immunocompetent, treatment-naïve rhesus macaques to be a uniquely informative model for human CRC.

Hybrid Cellular Nanovesicles Block PD-L1 Signal and Repolarize M2 Macrophages for Cancer Immunotherapy

The PD1/PD-L1 immune checkpoint blocking is a promising therapy, while immunosuppressive tumor microenvironment (TME) and poor tumor penetration of therapeutic antibodies limit its efficacy. Repolarization of tumor-associated macrophages (TAMs) offers a potential method to ameliorate immunosuppression of TME and further boost T cell antitumor immunity. Herein, hybrid cell membrane biomimetic nanovesicles (hNVs) are developed by fusing M1 macrophage-derived nanovesicles (M1-NVs) and PD1-overexpressed tumor cell-derived nanovesicles (PD1-NVs) to improve cancer immunotherapy. The M1-NVs promote the transformation of M2-like TAMs to M1-like phenotype and further increase the release of pro-inflammatory cytokines, resulting in improved immunosuppressive TME. Concurrently, the PD1-NVs block PD1/PD-L1 pathway, which boosts cancer immunotherapy when combined with M1-NVs. In a breast cancer mouse model, the hNVs efficiently accumulate at the tumor site after intravenous injection and significantly inhibit the tumor growth. Mechanically, the M1 macrophages and CD8+ T lymphocytes in TME increase by twofold after the treatment, indicating effective immune activation. These results suggest the hNVs as a promising strategy to integrate TME improvement with PD1/PD-L1 blockade for cancer immunotherapy.

A murine model to evaluate immunotherapy effectiveness for human Fanconi anemia-mutated acute myeloid leukemia

Fanconi anemia (FA)-mutated acute myeloid leukemia (AML) is a secondary AML with very poor prognosis and limited therapeutic options due to increased sensitivity to DNA-damaging agents. PD-1 immune checkpoint inhibitors upregulate T-cell killing of cancer cells and is a class of promising treatment for FA-AML. Here, we developed a novel FA-AML murine model that allows the study of human AML with a humanized immune system in order to investigate immunotherapeutic treatments in vivo. FA-AML1 cells and non-FA-mutated Kasumi-1 cells were injected into 8-10 week old NSG mice. Once leukemic engraftment was confirmed by HLA-DR expression in the peripheral blood, human peripheral blood mononuclear cells (hPBMCs) were injected into the mice. One week post-hPBMCs injection, Nivolumab (PD-1 inhibitor) or PBS vehicle control was administered to the mice bi-weekly. In our Nivolumab treated mice, FA-AML1, but not Kasumi-1-engrafted mice, had significantly prolonged overall survival. Both FA-AML1 and Kasumi-1 engrafted mice had decreased spleen weights. Higher leukemic infiltration into vital organs was observed in FA-AML1 engrafted mice compared to Kasumi-1 engrafted mice. In conclusion, our novel humanized murine model of FA-mutated AML is an attractive tool for supporting further studies and clinical trials using PD-1 inhibitors to treat FA-mutated AML.

Interferon gamma immunoPET imaging to evaluate response to immune checkpoint inhibitors

Introduction

We previously developed a 89Zr-labeled antibody-based immuno-positron emission tomography (immunoPET) tracer targeting interferon gamma (IFNγ), a cytokine produced predominantly by activated T and natural killer (NK) cells during pathogen clearance, anti-tumor immunity, and various inflammatory and autoimmune conditions. The current study investigated [89Zr]Zr-DFO-anti-IFNγ PET as a method to monitor response to immune checkpoint inhibitors (ICIs).

Methods

BALB/c mice bearing CT26 colorectal tumors were treated with combined ICI (anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and anti-programmed death 1 (PD-1)). The [89Zr]Zr-DFO-anti-IFNγ PET tracer, generated with antibody clone AN18, was administered on the day of the second ICI treatment, with PET imaging 72 hours later. Tumor mRNA was analyzed by quantitative reverse-transcribed PCR (qRT-PCR).

Results

We detected significantly higher intratumoral localization of [89Zr]Zr-DFO-anti-IFNγ in ICI-treated mice compared to untreated controls, while uptake of an isotype control tracer remained similar between treated and untreated mice. Interestingly, [89Zr]Zr-DFO-anti-IFNγ uptake was also elevated relative to the isotype control in untreated mice, suggesting that the IFNγ-specific tracer might be able to detect underlying immune activity in situ in this immunogenic model. In an efficacy experiment, a significant inverse correlation between tracer uptake and tumor burden was also observed. Because antibodies to cytokines often exhibit neutralizing effects which might alter cellular communication within the tumor microenvironment, we also evaluated the impact of AN18 on downstream IFNγ signaling and ICI outcomes. Tumor transcript analysis using interferon regulatory factor 1 (IRF1) expression as a readout of IFNγ signaling suggested there may be a marginal disruption of this pathway. However, compared to a 250 µg dose known to neutralize IFNγ, which diminished ICI efficacy, a tracer-equivalent 50 µg dose did not reduce ICI response rates.

Discussion

These results support the use of IFNγ PET as a method to monitor immune activity in situ after ICI, which may also extend to additional T cell-activating immunotherapies.

Immunotherapy-related biomarkers: Confirmations and uncertainties

Immunotherapy profoundly changed oncology treatment, becoming one of the main therapeutical strategies. Remarkable improvement has been achieved in survival outcomes, but the percentage of patients who benefit from immunotherapy is still limited. Only one-third of patients receiving immune checkpoint inhibitors (ICIs) achieve long-term response. Several patients are not responsive to treatment or relapse after an initial response. To date, programmed death-ligand 1, microsatellite instability, and tumor mutational burden are the three biomarkers validated to predict the ICIs response, but a single variable seems still insufficient in the patient's selection. Considering the substantial and increasing use of these drugs, the identification of new predictive biomarkers of ICI response is of paramount importance. We summarize the state of the art and the clinical use of immune biomarkers in oncology, highlighting the strength and weaknesses of currently approved biomarkers, describing the emerging tissues and circulating biomarkers, and outlining future perspectives.

Deep Learning Can Predict Bevacizumab Therapeutic Effect and Microsatellite Instability Directly from Histology in Epithelial Ovarian Cancer

Epithelial ovarian cancer (EOC) remains a significant cause of mortality among gynecologic cancers, with the majority of cases being diagnosed at an advanced stage. Before targeted therapies were available, EOC treatment relied largely on debulking surgery and platinum-based chemotherapy. Vascular endothelial growth factors have been identified as inducing tumor angiogenesis. According to several clinical trials, anti-vascular endothelial growth factor-targeted therapy with bevacizumab was effective in all phases of EOC treatment. However, there are currently no biomarkers accessible for regular therapeutic use despite the importance of patient selection. Microsatellite instability (MSI), caused by a deficiency of the DNA mismatch repair system, is a molecular abnormality observed in EOC associated with Lynch syndrome. Recent evidence suggests that angiogenesis and MSI are interconnected. Developing predictive biomarkers, which enable the selection of patients who might benefit from bevacizumab-targeted therapy or immunotherapy, is critical for realizing personalized precision medicine. In this study, we developed 2 improved deep learning methods that eliminate the need for laborious detailed image-wise annotations by pathologists and compared them with 3 state-of-the-art methods to not only predict the efficacy of bevacizumab in patients with EOC using mismatch repair protein immunostained tissue microarrays but also predict MSI status directly from histopathologic images. In prediction of therapeutic outcomes, the 2 proposed methods achieved excellent performance by obtaining the highest mean sensitivity and specificity score using MSH2 or MSH6 markers and outperformed 3 state-of-the-art deep learning methods. Moreover, both statistical analysis results, using Cox proportional hazards model analysis and Kaplan-Meier progression-free survival analysis, confirm that the 2 proposed methods successfully differentiate patients with positive therapeutic effects and lower cancer recurrence rates from patients experiencing disease progression after treatment (P < .01). In prediction of MSI status directly from histopathology images, our proposed method also achieved a decent performance in terms of mean sensitivity and specificity score even for imbalanced data sets for both internal validation using tissue microarrays from the local hospital and external validation using whole section slides from The Cancer Genome Atlas archive.

Imaging immune checkpoint networks in cancer tissues with supermultiplexed SERS nanoprobes

Combined immune checkpoint (ICP) inhibitors maximize immune response rates of patients compared to the single-drug treatment strategy in cancer immunotherapy, and prediction of such optimal combinations requires high-throughput imaging techniques and suitable data analysis. In this work, we report a rational strategy for predicting combined drugs of ICP inhibitors based on supermultiplexed surface-enhanced Raman scattering (SERS) imaging and correlation network analysis. To this end, we first built an ultrasensitive and supermultiplexed volume-active SERS (VASERS) nanoprobe platform, where Raman molecules are randomly arranged in 3D volumetric electromagnetic hotspots. By examining various bio-orthogonal Raman molecules with different electronic properties, we developed frequency modulation guidelines and achieved 32 resolvable colors in the Raman-silent region, the largest number of resolvable SERS colors demonstrated to date. We then demonstrated one-shot ten-color imaging of ICPs with high spectral resolution in clinical biopsies of breast cancer tissues, suggesting highly heterogeneous expression patterns of ICPs across tumor subtypes. Through correlation network analysis of these high-throughput Raman data, we investigated co-expression relationships among these ten-panel ICPs in cancer tissues and finally identified a variety of possible ICP combinations for synergistic immunotherapy of breast cancers, which may lead to novel therapeutical insights.

Beyond the Horizon: A Cutting-Edge Review of the Latest Checkpoint Inhibitors in Cancer Treatment

Immune checkpoint inhibitors (ICIs) have emerged as a revolutionary paradigm in oncology, offering a potent arsenal against various malignancies by harnessing the body's own immunological prowess. In a whirlwind of advancement, an abundance of new ICIs have come to light, rendering it a Herculean task for physicians to remain au courant with the rapidly evolving landscape. This comprehensive review meticulously explores the crescendo of clinical investigations and FDA approvals that have come to light during 2022 and 2023, showcasing the metamorphic impact of ICIs in cancer therapeutics. Delving into the pith of pivotal Phase 3 trials across diverse cancer types - including lung, renal, melanoma, and more - the review illuminates the significant strides made in enhancing patient outcomes, alongside the unveiling of novel ICIs that have garnered attention in the oncological community. The analysis extends to the notable presentations at the esteemed ESMO and ASCO conventions, providing a panoramic view of the contemporary advancements in ICI technology. Furthermore, the review underscores the imperative of continuous exploration in overcoming the extant challenges, such as the quest for reliable predictive biomarkers and the optimization of combinatorial strategies to surmount resistance and augment therapeutic efficacy. Through a holistic lens, this article elucidates the monumental impact of ICIs, marking a significant epoch in the odyssey towards rendering cancer a conquerable adversary.

Ibero-American Consensus Review and Incorporation of New Biomarkers for Clinical Practice in Colorectal Cancer

Advances in genomic technologies have significantly improved the management of colorectal cancer (CRC). Several biomarkers have been identified in CRC that enable personalization in the use of biologic agents that have shown to enhance the clinical outcomes of patients. However, technologies used for their determination generate massive amounts of information that can be difficult for the clinician to interpret and use adequately. Through several discussion meetings, a group of oncology experts from Spain and several Latin American countries reviewed the latest literature to provide practical recommendations on the determination of biomarkers in CRC based on their clinical experience. The article also describes the importance of looking for additional prognostic biomarkers and the use of histopathology to establish an adequate molecular classification. Present and future of immunotherapy biomarkers in CRC patients are also discussed, together with several techniques for marker determination, including liquid biopsy, next-generation sequencing (NGS), polymerase chain reaction (PCR), and fecal immunohistochemical tests. Finally, the role of Molecular Tumor Boards in the diagnosis and treatment of CRC is described. All of this information will allow us to highlight the importance of biomarker determination in CRC.

Review of the Immune Checkpoint Inhibitors in the Context of Cancer Treatment

Checkpoint proteins are an integral part of the immune system and are used by the tumor cells to evade immune response, which helps them grow uncontrollably. By blocking these proteins, immune checkpoint inhibitors can restore the capability of the immune system to attack cancer cells and stop their growth. These findings are backed by adequate clinical trial data and presently, several FDA-approved immune checkpoint inhibitors exist in the market for treating various types of cancers, including melanoma, hepatocellular, endometrial, lung, kidney and others. Their mode of action is inhibition by targeting the checkpoint proteins CTLA-4, PD-1, PD-L1, etc. They can be used alone as well as in amalgamation with other cancer treatments, like surgery, radiation or chemotherapy. Since these drugs target only specific immune system proteins, their side effects are reduced in comparison with the traditional chemotherapy drugs, but may still cause a few affects like fatigue, skin rashes, and fever. In rare cases, these inhibitors are known to have caused more serious side effects, such as cardiotoxicity, and inflammation in the intestines or lungs. Herein, we provide an overview of these inhibitors and their role as biomarkers, immune-related adverse outcomes and clinical studies in the treatment of various cancers, as well as present some future perspectives.

Engineering tumor-specific gene nanomedicine to recruit and activate T cells for enhanced immunotherapy

PD-1/PD-L1 blockade therapy that eliminates T-cell inhibition signals is successful, but poor benefits are often observed. Increasing T-cell infiltration and quantity of PD-1/PD-L1 inhibitors in tumor can improve efficacy but remains challenging. Here, we devise tumor-specific gene nanomedicines to mobilize tumor cells to secrete CXCL9 (T-cell chemokine) and anti-PD-L1 scFv (αPD-L1, PD-L1 blocking agent) for enhanced immunotherapy. The tyrosinase promoter-driven NP_Tyr-C9AP can specifically co-express CXCL9 and αPD-L1 in melanoma cells, thereby forming a CXCL9 gradient for T-cell recruitment and high intratumoral αPD-L1 concentration for enhancing T-cell activation. As a result, NP_Tyr-C9AP shows strong antimelanoma effects. Moreover, specific co-expression of CXCL9 and αPD-L1 in various tumor cells is achieved by replacing the tyrosinase promoter of NP_Tyr-C9AP with a survivin promoter, which increases T-cell infiltration and activation and therapeutic efficacy in multiple tumors in female mice. This study provides a strategy to maximize the immunotherapeutic outcome regardless of the heterogeneous tumor microenvironment.

Development and validation of blood tumor mutational burden reference standards

Tumor mutational burden (TMB), measured by exome or panel sequencing of tumor tissue or blood (bTMB), is a potential predictive biomarker for treatment benefit in patients with various cancer types receiving immunotherapy targeting checkpoint pathways. However, significant variability in TMB measurement has been observed. We developed contrived bTMB reference materials using DNA from tumor cell lines and donor-matched lymphoblastoid cell lines to support calibration and alignment across laboratories and platforms. Contrived bTMB reference materials were developed using genomic DNA from lung tumor cell lines blended into donor-matched lymphoblastoid cell lines at 0.5% and 2% tumor content, fragmented and size-selected to mirror the size profile of circulating cell-free tumor DNA with TMB scores of 7, 9, 20, and 26 mut/Mb. Variant allele frequency (VAF) and bTMB scores were assessed using PredicineATLAS and GuardantOMNI next-generation sequencing assays. DNA fragment sizes in the contrived reference samples were similar to those found within patient plasma-derived cell-free DNA, and mutational patterns aligned with those in the parental tumor lines. For the 7, 20, and 26 mut/Mb contrived reference samples with 2% tumor content, bTMB scores estimated using either assay aligned with expected scores from the parental tumor cell lines and showed good reproducibility. A bioinformatic filtration step was required to account for low-VAF artifact variants. We demonstrate the feasibility and challenges of producing and using bTMB reference standards across a range of bTMB levels, and how such standards could support the calibration and validation of bTMB platforms and help harmonization between panels and laboratories.

Immune Checkpoint Inhibitors for Solid Tumors in the Adjuvant Setting: Current Progress, Future Directions, and Role in Transplant Oncology

The rationale for administering immune checkpoint inhibitors (ICIs) in the adjuvant setting is to eradicate micro-metastases and, ultimately, prolong survival. Thus far, clinical trials have demonstrated that 1-year adjuvant courses of ICIs reduce the risk of recurrence in melanoma, urothelial cancer, renal cell carcinoma, non-small cell lung cancer, and esophageal and gastroesophageal junction cancers. Overall survival benefit has been shown in melanoma while survival data are still not mature in other malignancies. Emerging data also show the feasibility of utilizing ICIs in the peri-transplant setting for hepatobiliary malignancies. While ICIs are generally well-tolerated, the development of chronic immune-related adverse events, typically endocrinopathies or neurotoxicities, as well as delayed immune-related adverse events, warrants further scrutiny regarding the optimal duration of adjuvant therapy and requires a thorough risk-benefit determination. The advent of blood-based, dynamic biomarkers such as circulating tumor DNA (ctDNA) can help detect minimal residual disease and identify the subset of patients who would likely benefit from adjuvant treatment. In addition, the characterization of tumor-infiltrating lymphocytes, neutrophil-to-lymphocyte ratio, and ctDNA-adjusted blood tumor mutation burden (bTMB) has also shown promise in predicting response to immunotherapy. Until additional, prospective studies delineate the magnitude of overall survival benefit and validate the use of predictive biomarkers, a tailored, patient-centered approach to adjuvant ICIs that includes extensive patient counseling on potentially irreversible adverse effects should be routinely incorporated into clinical practice.

Diverse effects of obesity on antitumor immunity and immunotherapy

Currently, obesity is one of the biggest health burdens facing society because it causes several comorbidities, such as type 2 diabetes, atherosclerosis, and heart disease. Obesity is also linked to multiple types of cancer. Obesity is the second most common preventable cause of cancer after smoking; the rates of obesity are increasing worldwide, as are the rates of obesity-associated cancer. Multiple factors link obesity to cancer, such as increased levels of growth hormones and adipokines, gut dysbiosis, altered tumor metabolism, and chronic low-grade inflammation. More recently, obesity has been shown to also affect the immune response against cancer. In this review we discuss the interplay between obesity, the immune system, and cancer.

Association between serum baseline C1q and IgG levels and the efficacy of combined immunotherapy in patients with esophageal squamous cell carcinoma: a retrospective study

BACKGROUND

To assess the clinical value of serum complement component 1q (C1q) and immunoglobulin G (IgG) levels in predicting the response to combined immunotherapy in patients with esophageal squamous cell carcinoma.

METHODS

We conducted a retrospective study of 44 patients with esophageal squamous cell carcinoma who received combined immunotherapy in our hospital. Serum IgG and C1q levels were collected before and three weeks after immunotherapy treatment, together with other data on clinical and demographic characteristics.

RESULTS

Twenty seven patients (61.4%) showed partial response (PR), 13 (29.5%) stable disease (SD), and 4 (9.1%) progressive disease (PD). None of the patients presented complete response (CR). The PR group displayed lower IgG and higher C1q levels both before and after immunotherapy than patients showing SD or PD. The IgG reduction (59.3%) and C1q increment (70.3%) in the PR group three weeks post-treatment were significantly larger than those in patients showing SD or PD. Moreover, the pretreatment C1q level and the post-treatment change of C1q levels were strongly associated with the immunotherapy response.

CONCLUSIONS

High pre- and post-treatment C1q levels and reduced post-treatment IgG levels correlate with efficacy of combined immunotherapy in patients with esophageal squamous cell carcinoma. Serum baseline C1q level may predict immunotherapy response in such patients.

Immune-Checkpoint Inhibitors: A New Line of Attack in Triple-Negative Breast Cancer

Poor prognosis is a distinctive feature of triple-negative breast cancer (TNBC). Chemotherapy has long represented the main and unique treatment for patients with TNBC. Recently, immune checkpoint inhibitors (ICIs) were investigated in several clinical trials and were approved for clinical use in TNBC patients that express programmed cell death protein-1 (PD-1) in combination with chemotherapy in the first-line setting. ICIs are also being investigated in the neoadjuvant and adjuvant settings for TNBC. This chapter aims to discuss different ICIs used to treat all TNBC stages to date.

Mechanisms and Strategies to Overcome PD-1/PD-L1 Blockade Resistance in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is characterized by a high rate of systemic metastasis, insensitivity to conventional treatment and susceptibility to drug resistance, resulting in a poor patient prognosis. The immune checkpoint inhibitors (ICIs) represented by antibodies of programmed death receptor 1 (PD-1) and programmed death receptor ligand 1 (PD-L1) have provided new therapeutic options for TNBC. However, the efficacy of PD-1/PD-L1 blockade monotherapy is suboptimal immune response, which may be caused by reduced antigen presentation, immunosuppressive tumor microenvironment, interplay with other immune checkpoints and aberrant activation of oncological signaling in tumor cells. Therefore, to improve the sensitivity of TNBC to ICIs, suitable patients are selected based on reliable predictive markers and treated with a combination of ICIs with other therapies such as chemotherapy, radiotherapy, targeted therapy, oncologic virus and neoantigen-based therapies. This review discusses the current mechanisms underlying the resistance of TNBC to PD-1/PD-L1 inhibitors, the potential biomarkers for predicting the efficacy of anti-PD-1/PD-L1 immunotherapy and recent advances in the combination therapies to increase response rates, the depth of remission and the durability of the benefit of TNBC to ICIs.

Markers associated with genomic instability, immunogenicity and immune therapy responsiveness in Metaplastic carcinoma of the breast: Expression of γH2AX, pRPA2, P53, PD-L1 and tumor infiltrating lymphocytes in 76 cases

BACKGROUND

Metaplastic breast cancer (MpBC) is an aggressive subtype of breast carcinoma that is often resistant to conventional chemotherapy. Therefore, novel treatment strategies are urgently needed. Immune check point inhibitors have shown activity in programmed death-ligand 1 (PD-L1) - positive metastatic triple negative breast carcinoma (TNBC), which raises the possibility that immunotherapy may also be effective in MpBC as most of the MpBCs are triple negative. The aim of the present study was to assess genomic instability and immunogenicity in tumor specimens of patients with MpBC.

METHODS

A total of 76 patients diagnosed with MpBC over a 15-year period were included in the study. We performed immunohistochemical analyses for tumor cell PD-L1, immune cell PD-L1 and p53 on tissue microarrays (TMAs), analyzed stromal and intratumoral tumor infiltrating lymphocytes (TILs) from hematoxylin and eosin-stained (H&E) slides and scored gamma-H2AX (γH2AX) and phosphorylated-RPA2 (pRPA2) from whole tissue sections. We correlated marker expression with clinicopathologic features and clinical outcome.

RESULTS

All tumors expressed γH2AX and pRPA2 with median expressions of 43% and 44%. P53- (68%), tumor cell PD-L1- (59%) and immune cell PD-L1-positivity (62%) were common in MpBCs. Median stromal TIL and intratumoral TIL counts were 5% and 0. The spindle and squamous cell carcinomas expressed the highest levels of PD-L1 and TILs, and carcinoma with mesenchymal differentiation the lowest.

CONCLUSIONS

MpBC appears to be an immunogenic cancer with high genomic instability and frequent PD-L1-positivity, implying that check point inhibitors might be effective in MpBC. Expression levels of PD-L1 and TILs varied across different histologic subtypes, suggesting that immunotherapy might be less effective in carcinoma with mesenchymal differentiation.

An immune risk score predicts progression-free survival of melanoma patients in South China receiving anti-PD-1 inhibitor therapy-a retrospective cohort study examining 66 circulating immune cell subsets

Introduction

Immune checkpoint blockade inhibitor (ICI) therapy offers significant survival benefits for malignant melanoma. However, some patients were observed to be in disease progression after the first few treatment cycles. As such, it is urgent to find convenient and accessible indicators that assess whether patients can benefit from ICI therapy.

Methods

In the training cohort, flow cytometry was used to determine the absolute values of 66 immune cell subsets in the peripheral blood of melanoma patients (n=29) before treatment with anti-PD-1 inhibitors. The least absolute shrinkage and selection operator (LASSO) Cox regression model was followed for the efficacy of each subset in predicting progression-free survival. Then we validated the performance of the selected model in validation cohorts (n=20), and developed a nomogram for clinical use.

Results

A prognostic immune risk score composed of CD1c⁺ dendritic cells and three subsets of T cells (CD8⁺CD28⁺, CD3⁺TCRab⁺HLA-DR⁺, CD3⁺TCRgd⁺HLA-DR⁺) with a higher prognostic power than individual features (AUC = 0.825). Using this model, patients in the training cohort were divided into high- and low-risk groups with significant differences in mean progression-free survival (3.6 vs. 12.3 months), including disease control rate (41.2% vs. 91.7%), and objective response rate (17.6% vs. 41.6%). Integrating four-immune cell-subset based classifiers and three clinicopathologic risk factors can help to predict which patients might benefit from anti-PD-1 antibody inhibitors and remind potential non-responders to pursue effective treatment options in a timely way.

Conclusions

The prognostic immune risk score including the innate immune and adaptive immune cell populations could provide an accurate prediction efficacy in malignant melanoma patients with ICI therapy.

Targeting GNAQ/11 through PKC inhibition in uveal melanoma

Uveal melanoma is a rare malignancy affecting 5.1 patients/million per year with definitive treatment options of enucleation or radiation therapy to the primary tumor. Unfortunately, no FDA-approved systemic therapies exist for patients in the adjuvant or metastatic setting. Molecular profiling over the past decade has helped define uveal melanomas by characteristic mutations: GNAQ, GNA11, BAP1, SF3B1, and EIF1AX mutations. GNAQ/11 mutations are present in over 90% of patients with uveal melanoma and lead to signal transduction through G-protein coupled receptors to downstream growth factors. PKC inhibition has been an active area of investigation targeting this pathway specific to uveal melanoma. Several molecules have been developed and evaluated in clinical trials. Responses have been noted but clinical development has also yielded multiple toxicities and pathways of resistance limiting both breadth and durability of responses leading to combination therapy approaches. PKC inhibition remains an active and encouraging area of research to determine effective therapies for patients with uveal melanoma.

Machine learning on syngeneic mouse tumor profiles to model clinical immunotherapy response

Most patients with cancer are refractory to immune checkpoint blockade (ICB) therapy, and proper patient stratification remains an open question. Primary patient data suffer from high heterogeneity, low accessibility, and lack of proper controls. In contrast, syngeneic mouse tumor models enable controlled experiments with ICB treatments. Using transcriptomic and experimental variables from >700 ICB-treated/control syngeneic mouse tumors, we developed a machine learning framework to model tumor immunity and identify factors influencing ICB response. Projected on human immunotherapy trial data, we found that the model can predict clinical ICB response. We further applied the model to predicting ICB-responsive/resistant cancer types in The Cancer Genome Atlas, which agreed well with existing clinical reports. Last, feature analysis implicated factors associated with ICB response. In summary, our computational framework based on mouse tumor data reliably stratified patients regarding ICB response, informed resistance mechanisms, and has the potential for wide applications in disease treatment studies.

Predictive and prognostic values of tumor infiltrating lymphocytes in breast cancers treated with neoadjuvant chemotherapy: A meta-analysis

BACKGROUND

This meta-analysis assessed the predictive and prognostic value of tumor infiltrating lymphocytes (TILs) in neoadjuvant chemotherapy (NACT) treated breast cancer and an optimal threshold for predicting pathologic complete response (pCR).

METHODS

A systematic search of PubMed, EMBASE and Web of Science electronic databases was conducted to identify eligible studies published before April 2022. Either a fixed or random effects model was applied to estimate the pooled hazard ratio (HR) and odds ratio (OR) for prognosis and predictive values of TILs in breast cancer patients treated with NACT. The study is registered with PROSPERO (CRD42020221521).

RESULTS

A total of 29 published studies were eligible. Increased levels of TILs predicted response to NACT in HER2 positive breast cancer (OR = 2.54 95%CI, 1.50-4.29) and triple negative breast cancer (TNBC) (OR = 3.67, 95%CI, 1.93-6.97), but not for hormone receptor (HR) positive breast cancer (OR = 1.68, 95 %CI, 0.67-4.25). A threshold of 20% of H & E-stained TILs was associated with prediction of pCR in both HER2 positive breast cancer (P = 0.035) and TNBC (P = 0.001). Moreover, increased levels of TILs (either iTILs or sTILs) were associated with survival benefit in HER2-positive breast cancer and TNBC. However, an increased level of TILs was not a prognostic factor for survival in HR positive breast cancer (pooled HR = 0.64, 95%CI: 0.03-14.1, P = 0.78).

CONCLUSIONS

Increased levels of TILs were associated with increased rates of response to NACT and improved prognosis for the molecular subtypes of TNBC and HER2-positive breast cancer, but not for patients with HR positive breast cancer. A threshold of 20% TILs was the most powerful outcome prognosticator of pCR.

The tumor microenvironment and prognostic role of autophagy- and immune-related genes in bladder cancer

BACKGROUND: Autophagy-related genes and immune-related genes contribute significantly to the initiation and prognosis of bladder cancer (BLCA). OBJECTIVE: We aimed to explore differentially expressed autophagy-related genes (DEARGs) and immune-related genes (DEIRGs) in BLCA to create a prognostic risk assessment model and gain some insights into BLCA’s molecular underpinnings. METHODS: The prognostic DEARGs and DEIRGs were evaluated for BLCA through The Cancer Genome Atlas (TCGA) database (n= 399) and GSE13507 dataset (n= 165). The BLCA risk model was constructed and verified. The immune score, stromal score, and estimate score in different risk groups were calculated by the ESTIMATE algorithm. Immune infiltration levels were assessed by a single sample gene set enrichment analysis (GSEA) algorithm. RESULTS: In the risk model, AURKA, ACTC1, MYLK, PDGFD, PDGFRA and TNC were significantly associated with the overall survival. The pathways in cancer, T cell receptor signaling pathway and B cell receptor signaling pathway were significantly gathered in the high-risk group. Moreover, the risk score was significantly correlated with infiltrating immune cells, expression of critical immune checkpoints and mismatch repair genes including MSH6, MLH1, and MSH2. CONCLUSIONS: In this study, three DEARGs (AURKA, ACTC1, MYLK) and three DEIRGs (PDGFD, PDGFRA, TNC) were demonstrated to be potential prognostic biomarkers for BLCA patients through bioinformatics methods, which might be novel therapeutic targets and prognostic markers for BLCA, in follow up studies, we will combine experiments to verify this.

HSP70-Promoter-Driven CRISPR/Cas9 System Activated by Reactive Oxygen Species for Multifaceted Anticancer Immune Response and Potentiated Immunotherapy

To address the low response rate to immune checkpoint blockade (ICB) therapy, we propose a specific promoter-driven CRISPR/Cas9 system, F-PC/pHCP, that achieves permanent genomic disruption of PD-L1 and elicits a multifaceted anticancer immune response to potentiate immunotherapy. This system consists of a chlorin e6-encapsulated fluorinated dendrimer and HSP70-promoter-driven CRISPR/Cas9. F-PC/pHCP under 660 nm laser activated the HSP70 promoter and enabled the specific expression of the Cas9 protein to disrupt the PD-L1 gene, preventing immune escape. Moreover, F-PC/pHCP also induced immunogenic cell death (ICD) of tumor cells and reprogrammed the immunosuppressive tumor microenvironment. Overall, this specific promoter-driven CRISPR/Cas9 system showed great anticancer efficacy and, more importantly, stimulated an immune memory response to inhibit distant tumor growth and lung metastasis. This CRISPR/Cas9 system represents an alternative strategy for ICB therapy as well as enhanced cancer immunotherapy.

Ligands stimulating antitumour immunity as the next G-quadruplex challenge

G-quadruplex (G4) binders have been investigated to discover new anticancer drugs worldwide in past decades. As these ligands are generally not highly cytotoxic, the discovery rational was mainly based on increasing the cell-killing potency. Nevertheless, no G4 binder has been shown yet to be effective in cancer patients. Here, G4 binder activity at low dosages will be discussed as a critical feature to discover ligands with therapeutic effects in cancer patients. Specific effects of G4 binders al low doses have been reported to occur in cancer and normal cells. Among them, genome instability and the stimulation of cytoplasmic processes related to autophagy and innate immune response open to the use of G4 binders as immune-stimulating agents. Thus, we propose a new rational of drug discovery, which is not based on cytotoxic potency but rather on immune gene activation at non-cytotoxic dosage.

Overcoming the cardiac toxicities of cancer therapy immune checkpoint inhibitors

Immune checkpoint inhibitors (ICIs) have led recent advances in the field of cancer immunotherapy improving overall survival in multiple malignancies with abysmal prognoses prior to their introduction. The remarkable efficacy of ICIs is however limited by their potential for systemic and organ specific immune-related adverse events (irAEs), most of which present with mild to moderate symptoms that can resolve spontaneously, with discontinuation of therapy or glucocorticoid therapy. Cardiac irAEs however are potentially fatal. The understanding of autoimmune cardiotoxicity remains limited due to its rareness. In this paper, we provide an updated review of the literature on the pathologic mechanisms, diagnosis, and management of autoimmune cardiotoxicity resulting from ICIs and their combinations and provide perspective on potential strategies and ongoing research developments to prevent and mitigate their occurrence.

Clinical significance for diagnosis and prognosis of POP1 and its potential role in breast cancer: a comprehensive analysis based on multiple databases

Background: Breast cancer (BC) is one of the most common cancers in women. The discovery of available biomarkers is crucial for early diagnosis and improving prognosis. The effect of POP1 in BC remains unrevealed. Our study aims to explore the expression of POP1 in BC and demonstrate its clinical significance and potential molecular mechanisms.

Methods: The Cancer Genome Atlas (TCGA) BC cohort transcriptome data and corresponding clinical information were downloaded. GSE42568 cohort, GSE162228 cohort, GSE7904 cohort, and GSE161533 cohort in the Gene Expression Omnibus (GEO) database were used as verification groups. R software and several web tools were used for statistical analysis. Moreover, the proliferation, transwell, wound healing experiments, and flow cytometry were used for in vitro investigation.

Results: Compared with normal breast tissue, POP1 expression was up-regulated in BC tissue with a higher mutation rate. POP1 had good diagnostic value for BC and could be utilized as a new marker. POP1 was significantly correlated with multiple pathways in BC and played an important role in the immune infiltration of BC. High-POP1 expression patients were more prone to be responded to immunotherapy and had a significantly higher percentage of immunotherapy response rate. Moreover, POP1 promoted proliferation and migration and inhibited apoptosis in BC cells.

Conclusions: POP1 expression was up-regulated in BC and was associated with a poor prognosis. Patients with high-POP1 expression were more likely to be responded to immunotherapy. Our study can provide a potential marker POP1 for BC, which is beneficial in the diagnosis and treatment of BC.

Radiation and immune checkpoint inhibitor-mediated pneumonitis risk stratification in patients with locally advanced non-small cell lung cancer: role of functional lung radiomics?

BACKGROUND

Patients undergoing chemoradiation and immune checkpoint inhibitor (ICI) therapy for locally advanced non-small cell lung cancer (NSCLC) experience pulmonary toxicity at higher rates than historical reports. Identifying biomarkers beyond conventional clinical factors and radiation dosimetry is especially relevant in the modern cancer immunotherapy era. We investigated the role of novel functional lung radiomics, relative to functional lung dosimetry and clinical characteristics, for pneumonitis risk stratification in locally advanced NSCLC.

METHODS

Patients with locally advanced NSCLC were prospectively enrolled on the FLARE-RT trial (NCT02773238). All received concurrent chemoradiation using functional lung avoidance planning, while approximately half received consolidation durvalumab ICI. Within tumour-subtracted lung regions, 110 radiomics features (size, shape, intensity, texture) were extracted on pre-treatment [^99mTc]MAA SPECT/CT perfusion images using fixed-bin-width discretization. The performance of functional lung radiomics for pneumonitis (CTCAE v4 grade 2 or higher) risk stratification was benchmarked against previously reported lung dosimetric parameters and clinical risk factors. Multivariate least absolute shrinkage and selection operator Cox models of time-varying pneumonitis risk were constructed, and prediction performance was evaluated using optimism-adjusted concordance index (c-index) with 95% confidence interval reporting throughout.

RESULTS

Thirty-nine patients were included in the study and pneumonitis occurred in 16/39 (41%) patients. Among clinical characteristics and anatomic/functional lung dosimetry variables, only the presence of baseline chronic obstructive pulmonary disease (COPD) was significantly associated with the development of pneumonitis (HR 4.59 [1.69-12.49]) and served as the primary prediction benchmark model (c-index 0.69 [0.59-0.80]). Discrimination of time-varying pneumonitis risk was numerically higher when combining COPD with perfused lung radiomics size (c-index 0.77 [0.65-0.88]) or shape feature classes (c-index 0.79 [0.66-0.91]) but did not reach statistical significance compared to benchmark models (p > 0.26). COPD was associated with perfused lung radiomics size features, including patients with larger lung volumes (AUC 0.75 [0.59-0.91]). Perfused lung radiomic texture features were correlated with lung volume (adj R² = 0.84-1.00), representing surrogates rather than independent predictors of pneumonitis risk.

CONCLUSIONS

In patients undergoing chemoradiation with functional lung avoidance therapy and optional consolidative immune checkpoint inhibitor therapy for locally advanced NSCLC, the strongest predictor of pneumonitis was the presence of baseline chronic obstructive pulmonary disease. Results from this novel functional lung radiomics exploratory study can inform future validation studies to refine pneumonitis risk models following combinations of radiation and immunotherapy. Our results support functional lung radiomics as surrogates of COPD for non-invasive monitoring during and after treatment. Further study of clinical, dosimetric, and radiomic feature combinations for radiation and immune-mediated pneumonitis risk stratification in a larger patient population is warranted.

Tumor infiltrating lymphocytes (TILs) as a predictive biomarker of response to checkpoint blockers in solid tumors: a systematic review

Immunotherapy is a standard of care in many solid tumors but many patients derive limited benefit from it. There is increasing interest toward tumor infiltrating lymphocytes (TILs) since their presence may be related with good outcomes from treatment with immune checkpoint blockers. We aimed at systematically reviewing existing evidence about the role of TILs as possible predictors of response to immunotherapy in solid tumors. We reviewed 1193 records published from January 2010 until December 2021. Associations between TILs and outcomes were observed mainly in melanoma and breast cancer. Overall survival and overall response rate for advanced disease and pathological complete response for early-phase tumors were the most commonly assessed endpoints. No definitive conclusion can be drawn on the predictive role of TILs. Additional studies, exploiting data from prospective, randomized clinical trials should further evaluate TILs also with the aim of identifying standard cut-off to differentiate between high and low TILs.

Identification of Crucial Gene Modules Related to the Efficiency of Anti-PD-1/PD-L1 Therapy and Comprehensive Analyses of a Novel Signature Based on These Modules

Biomarker development for clinical checkpoint inhibition is still in its early stages. It is critical to determine the cause of the lack of a long-term response in patients after immune checkpoint blockade (ICB) treatment and to develop composite biomarkers or signatures to improve personalized approaches. Three modules that were significantly correlated with the immunotherapeutic response were identified. Stimulatory pathways of cellular immunity, extracellular matrix formation-related pathways, and ATP metabolism-related pathways were enriched. Two distinct transcriptional subtypes were determined. Tumor microenvironment (TME) characteristics were highly correlated with “hot” and “cold” tumors. The ICB score was significantly correlated with clinical characteristics including age, Breslow depth, Clerk level, AJCC stage, and T stage. Meanwhile, a low ICB score is characterized by increased activation of immunity, a higher level of immune infiltration, and immune molecule expression. The ICB score showed a robust ability to predict melanoma prognosis in the discovery, internal validation, and external validation cohorts. In addition, a low ICB score was linked to a higher CR/PR rate in the immunotherapeutic cohort. The ICB score could reflect the pre-existing immune features and the expression pattern of “Cold” versus “Hot” tumors in melanoma patients. Thus, it has the potential to serve as a reliable predictor of melanoma prognosis and response to ICB therapy.

Therapeutic pattern and progress of neoadjuvant treatment for triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a heterogeneous disease, accounting for about 15.0-20.0% of all breast cancer cases. TNBC is associated with early recurrence and metastasis, strong invasiveness and a poor prognosis. Chemotherapy is currently the mainstay of treatment for TNBC, and achievement of a pathological complete response is closely associated with a long-term good prognosis. Improving the long-term prognosis in patients with TNBC is a challenge in breast cancer treatment, and more clinical evidence is needed to guide the choice of treatment strategies. The current study reviews the conventional treatment modality for TNBC and the selection of neoadjuvant chemotherapy (NACT) regimens available. The research progress on optimizing NACT regimens is also reviewed, and the uniqueness of the treatment of this breast cancer subtype is emphasized, in order to provide reference for the clinical practice and research with regard to TNBC treatment.

Progress and Prospect of Immunotherapy for Triple-Negative Breast Cancer

Breast cancer is the most commonly diagnosed cancer (estimated 2.3 million new cases in 2020) and the leading cause of cancer death (estimated 685,000 deaths in 2020) in women globally. Breast cancers have been categorized into four major molecular subtypes based on the immunohistochemistry (IHC) expression of classic hormone and growth factor receptors including the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), as well as a proliferation marker Ki-67 protein expression. Triple-negative breast cancer (TNBC), a breast cancer subtype lacking ER, PR, and HER2 expression, is associated with a high metastatic potential and poor prognosis. TNBC accounts for approximately only 15%–20% of new breast cancer diagnoses; it is responsible for most breast cancer–related deaths due to the lack of targeted treatment options for this patient population, and currently, systemic chemotherapy, radiation, and surgical excision remain the major treatment modalities for these patients with TNBC. Although breast cancer patients in general do not have a robust response to the immunotherapy, a subset of TNBC has been demonstrated to have high tumor mutation burden and high tumor-infiltrating lymphocytes, resembling the features observed on melanoma or lung cancers, which can benefit from the treatment of immune checkpoint inhibitors (ICIs). Therefore, the immunogenic nature of this aggressive disease has presented an opportunity for the development of TNBC-targeting immunotherapies. The recent US Food and Drug Administration approval of atezolizumab in combination with the chemotherapeutic agent nab-paclitaxel for the treatment of PD-L1-positive unresectable, locally advanced, or metastatic TNBC has led to a new era of immunotherapy in TNBC treatment. In addition, immunotherapy becomes an active research area, both in the cancer biology field and in the oncology field. In this review, we will extend our coverage on recent discoveries in preclinical research and early results in clinical trials from immune molecule-based therapy including cytokines, monoclonal antibodies, antibody–drug conjugates, bi-specific or tri-specific antibodies, ICIs, and neoantigen cancer vaccines; oncolytic virus-based therapies and adoptive immune cell transfer–based therapies including TIL, chimeric antigen receptor-T (CAR-T), CAR-NK, CAR-M, and T-cell receptor-T. In the end, we will list a series of the challenges and opportunities in immunotherapy prospectively and reveal novel technologies such as high-throughput single-cell sequencing and CRISPR gene editing-based screening to generate new knowledges of immunotherapy.

Longitudinal plasma proteomic profiling of patients with non-small cell lung cancer undergoing immune checkpoint blockade

Background

Immune checkpoint inhibitors (ICIs) have revolutionized the cancer therapy landscape due to long-term benefits in patients with advanced metastatic disease. However, robust predictive biomarkers for response are still lacking and treatment resistance is not fully understood.

Methods

We profiled approximately 800 pre-treatment and on-treatment plasma proteins from 143 ICI-treated patients with non-small cell lung cancer (NSCLC) using ELISA-based arrays. Different clinical parameters were collected from the patients including specific mutations, smoking habits, and body mass index, among others. Machine learning algorithms were used to identify a predictive signature for response. Bioinformatics tools were used for the identification of patient subtypes and analysis of differentially expressed proteins and pathways in each response group.

Results

We identified a predictive signature for response to treatment comprizing two proteins (CXCL8 and CXCL10) and two clinical parameters (age and sex). Bioinformatic analysis of the proteomic profiles identified three distinct patient clusters that correlated with multiple parameters such as response, sex and TNM (tumors, nodes, and metastasis) staging. Patients who did not benefit from ICI therapy exhibited significantly higher plasma levels of several proteins on-treatment, and enrichment in neutrophil-related proteins.

Conclusions

Our study reveals potential biomarkers in blood plasma for predicting response to ICI therapy in patients with NSCLC and sheds light on mechanisms underlying therapy resistance.

A novel immune checkpoint siglec-15 antibody inhibits LUAD by modulating mφ polarization in TME

BACKGROUND

Siglec-15 (S15) is a type-I transmembrane protein and is considered a new candidate of immune checkpoint inhibitor for cancer immunotherapy.

METHODS

In the present study, we first constructed and characterized a chimeric S15-specific monoclonal antibody (S15-4E6A). Then, the antitumor effectiveness and modulatory role of S15-4E6A in macrophages (mφs) were explored in vitro and in vivo. Finally, the underlying mechanism by which S15mAb inhibits LUAD was preliminarily explored.

RESULTS

The results demonstrated the successful construction of S15-4E6A, and S15-4E6A exerted an efficacious tumor-inhibitory effect on LUAD cells and xenografts. S15-4E6A could promote M1-mφ polarization while inhibiting M2-mφ polarization, both in vitro and in vivo.

CONCLUSIONS

S15-based immunotherapy that functions by modulating mφ polarization may be a promising strategy for the treatment of S15-positive LUAD.

Immune Checkpoint Blockades in Triple-Negative Breast Cancer: Current State and Molecular Mechanisms of Resistance

Immune checkpoint blockades (ICBs) have revolutionized cancer treatment. Recent studies have revealed a subset of triple-negative breast cancer (TNBC) to be considered as an immunogenic breast cancer subtype. Characteristics of TNBC, such as higher mutation rates and number of tumor-infiltrating immune cells, render the immunogenic phenotypes. Consequently, TNBCs have shown durable responses to ICBs such as atezolizumab and pembrolizumab in clinic. However, a significant number of TNBC patients do not benefit from these therapies, and mechanisms of resistance are poorly understood. Here, we review biomarkers that predict the responsiveness of TNBCs to ICB and recent advances in delineating molecular mechanisms of resistance to ICBs.

Concordance Study of a 520-Gene Next-Generation Sequencing-Based Genomic Profiling Assay of Tissue and Plasma Samples

INTRODUCTION

Next-generation sequencing (NGS) enables simultaneous detection of actionable somatic variants and estimation of genomic signatures such as tumor mutational burden (TMB) or microsatellite instability (MSI) status, which empowers therapeutic decisions in clinical oncology.

OBJECTIVE

Our retrospective study investigated the clinical performance of somatic variant detection in paired tissue and blood samples using a large targeted gene panel, the OncoScreen Plus, which interrogates 520 cancer-related genes.

METHODS

We analyzed sequencing data derived from paired tissue and blood samples of 3005 patients spanning 20 solid tumor types, including lung (n = 1971), gastrointestinal (n = 625), breast (n = 120) and gynecological (n = 110), genitourinary (n = 38), and other cancers (n = 141).

RESULTS

Across tumor types, the OncoScreen Plus panel achieved a high tissue detection rate, with an average of 97.9%. The average plasma detection rate was 72.2%, with an average tissue concordance rate of 36.6%. Considering all variant types, the plasma assay yielded an average sensitivity/true positive rate of 45.7%, with a positive predictive value of 64.7% relative to tissue assay. Pearson correlation analysis revealed a strong correlation in TMB estimated from blood and tissue samples (correlation coefficient 0.845, R² = 0.756). MSI-high status was identified in five tumor types, including endometrial cancer (28.6%), colorectal cancer (2.5%), ovarian cancer (2.0%), gastric cancer (1.5%), and lung adenocarcinoma (0.2%).

CONCLUSION

Paired tumor and blood samples from a large cohort of patients spanning 20 tumor types demonstrated that the OncoScreen Plus is a reliable pan-cancer panel for the accurate detection of somatic variants and genomic signatures that could guide individualized treatment strategies to improve the care of patients with advanced cancer.

Transcriptional and post-transcriptional regulation of checkpoint genes on the tumour side of the immunological synapse

Cancer is a disease of the genome, therefore, its development has a clear Mendelian component, demonstrated by well-studied genes such as BRCA1 and BRCA2 in breast cancer risk. However, it is known that a single genetic variant is not enough for cancer to develop leading to the theory of multistage carcinogenesis. In many cases, it is a sequence of events, acquired somatic mutations, or simply polygenic components with strong epigenetic effects, such as in the case of brain tumours. The expression of many genes is the product of the complex interplay between several factors, including the organism’s genotype (in most cases Mendelian-inherited), genetic instability, epigenetic factors (non-Mendelian-inherited) as well as the immune response of the host, to name just a few. In recent years the importance of the immune system has been elevated, especially in the light of the immune checkpoint genes discovery and the subsequent development of their inhibitors. As the expression of these genes normally suppresses self-immunoreactivity, their expression by tumour cells prevents the elimination of the tumour by the immune system. These discoveries led to the rapid growth of the field of immuno-oncology that offers new possibilities of long-lasting and effective treatment options. Here we discuss the recent advances in the understanding of the key mechanisms controlling the expression of immune checkpoint genes in tumour cells.

The interaction of p53 and DNA repair gene mutations and their impact on tumor mutation burden and immune response in human malignancies

P53 suppresses tumorigenesis through multiple cellular functions/mechanisms, including genomic stability surveillance. Recently, it has also be reported for its role in cancer immune response modulation. Deficiency in DNA repair pathways lead to the accumulation of genomic alterations and tumor mutation burden and in consequence resulting in the activation of immune response. We investigated the interaction of p53 and DNA repair gene mutations and their impact on tumor mutation burden and immune response in human malignancies by mining cBioPortal data of a range of human cancers. We found that in the majority of human cancers, p53 mutations are equally distributed between DNA repair gene mutation positive and negative cases and in a number of human cancers, p53 and DNA repair gene mutations have a tendency of co-occurrence. Only in colorectal cancer, there is a tendency of 'mutual exclusivity' of mutations in p53 and DNA repair genes. In most tumors, p53 and DNA repair gene mutations have synergistic/additive effect in increasing tumor mutation burden, but not in colorectal cancer where they are mutually exclusive. The impact of p53 and DNA repair gene mutations and their interaction on tumor microenvironment immune cells are complex and tumor type specific and not always correlated with tumor mutation burden. In colorectal cancers, these two types of mutations resulted in similar immune cell subpopulation changes and in tumors where the mutations have a tendency of co-occurrence, p53 showed dominant roles on immune response, although they can also counter-act each other for their effect on certain immune cell subtypes.

Weighted Gene Coexpression Network Analysis Identifies TBC1D10C as a New Prognostic Biomarker for Breast Cancer

Background

Immune checkpoint inhibitors are a promising therapeutic strategy for breast cancer (BRCA) patients. The tumor microenvironment (TME) can downregulate the immune response to cancer therapy. Our study is aimed at finding a TME-related biomarker to identify patients who might respond to immunotherapy.

Method

We downloaded raw data from several databases including TCGA and MDACC to identify TME hub genes associated with overall survival (OS) and the progression-free interval (PFI) by WGCNA. Correlations between hub genes and either tumor-infiltrating immune cells or immune checkpoints were conducted by ssGSEA.

Result

TME-related green and black modules were selected by WGCNA to further screen hub genes. Random forest and univariate and multivariate Cox regressions were applied to screen hub genes (MYO1G, TBC1D10C, SELPLG, and LRRC15) and construct a nomogram to predict the survival of BRCA patients. The C-index for the nomogram was 0.713. A DCA of the predictive model revealed that the net benefit of the nomogram was significantly higher than others and the calibration curve demonstrated a good performance by the nomogram. Only TBC1D10C was correlated with both OS and the PFI (both p values < 0.05). TBC1D10C also had a high positive association with tumor-infiltrating immune cells and common immune checkpoints (PD-1, CTLA-4, and TIGIT).

Conclusion

We constructed a TME-related gene signature model to predict the survival probability of BRCA patients. We also identified a hub gene, TBC1D10C, which was correlated with both OS and the PFI and had a high positive association with tumor-infiltrating immune cells and common immune checkpoints. TBC1D10C may be a new biomarker to select patients who may benefit from immunotherapy.

Which role for predictors of response to immune checkpoint inhibitors in hepatocellular carcinoma?

INTRODUCTION

Hepatocellular carcinoma (HCC) remains a frequently diagnosed malignancy worldwide, still representing an important cause of cancer-related death. Recent years have seen the emergence of novel systemic treatments for HCC patients, including immune checkpoint inhibitors (ICIs). Nonetheless, several questions regarding HCC immunotherapy remain unanswered, especially in terms of biochemical predictors of response.

AREAS COVERED

In the current paper, we will discuss available evidence regarding predictive biomarkers of response to HCC immunotherapy. A literature search was conducted in January 2022 of Pubmed/Medline, Cochrane library, and Scopus databases.

EXPERT OPINION

The identification of predictive biomarkers represents an unmet need in HCC patients receiving ICIs. The HCC medical community is called to further efforts aimed to elucidate the effective role of PD-L1 expression, TMB, MSI, gut microbiota, and other emerging biomarkers.

The Expression Pattern of Ferroptosis-Related Genes in Colon Adenocarcinoma: Highly Correlated to Tumor Microenvironment Characteristics

In the latest literatures, ferroptosis caused by T cells in cancerous cells provided new insights of improving curative effect of the PD-1/PD-L1 antibody. The microenvironment on which tumor cells develop and survive was also emphasized as its crucial role in tumor occurrence, development, metastasis and immune escape. Thus, the interaction of ferroptosis related genes and tumor microenvironment (TME) was urgently be detected in a comprehensive perspective. We comprehensively evaluated the transcriptional feature of ferroptosis related genes in colon adenocarcinoma (COAD), and systematically associated these ferroptosis subtypes with DNA damage repair (DDR) and TME characteristics. We found two unique patterns of ferroptosis characterized by distinct biological pathways activation. We also demonstrated that FRG score constructed based on ferroptosis subtypes has a significant correlation with prognosis of colon cancer and could act as an independent prognostic biomarker for predicting patients’ survival. The higher immune infiltrating level, immune functional pathways activation was observed in the high FRG score group. Furthermore, these results were verified by an independent external GEO cohort. This work revealed ferroptosis was highly associated with TME complexity and diversity. A novel ferroptosis subtypes related gene scoring system can be used for prognostic prediction in COAD. Targeting ferroptosis may be a therapeutic alternative for COAD.

Identification of Novel Molecular Therapeutic Targets and Their Potential Prognostic Biomarkers Based on Cytolytic Activity in Skin Cutaneous Melanoma

Skin cutaneous melanoma (SKCM) attracts attention worldwide for its extremely high malignancy. A novel term cytolytic activity (CYT) has been introduced as a potential immunotherapy biomarker associated with counter-regulatory immune responses and enhanced prognosis in tumors. In this study, we extracted all datasets of SKCM patients, namely, RNA sequencing data and clinical information from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database, conducted differential expression analysis to yield 864 differentially expressed genes (DEGs) characteristic of CYT and used non-negative matrix factorization (NMF) method to classify molecular subtypes of SKCM patients. Among all genes, 14 hub genes closely related to prognosis for SKCM were finally screen out. Based on these genes, we constructed a 14-gene prognostic risk model and its robustness and strong predictive performance were further validated. Subsequently, the underlying mechanisms in tumor pathogenesis and prognosis have been defined from a number of perspectives, namely, tumor mutation burden (TMB), copy number variation (CNV), tumor microenvironment (TME), infiltrating immune cells, gene set enrichment analysis (GSEA) and immune checkpoint inhibitors (ICIs). Furthermore, combined with GTEx database and HPA database, the expression of genes in the model was verified at the transcriptional level and protein level, and the relative importance of genes in the model was described by random forest algorithm. In addition, the model was used to predict the difference in sensitivity of SKCM patients to chemotherapy and immunotherapy. Finally, a nomogram was constructed to better aid clinical diagnosis.

Phase 2 single arm study of nivolumab and ipilimumab (Nivo/Ipi) in previously treated classical Kaposi Sarcoma (cKS)

BACKGROUND

Classical Kaposi Sarcoma (cKS) is a rare HHV8-associated sarcoma with limited treatment options. We evaluated the efficacy and safety of nivolumab in combination with ipilimumab (Nivo/Ipi) in patients with previously treated progressive cKS.

PATIENTS AND METHODS

cKS pts with progressive disease after > 1 lines of systemic therapy and measurable disease by PET/CT and/or physical examination received nivolumab 240mg every two weeks and ipilimumab 1mg/kg every six weeks until progression or toxicity for a maximum of 24 months. The primary endpoint was overall response rate (ORR); secondary endpoints included 6-months progression free survival rate (PFS) and safety. Immune correlates were explored using IHC, DNAseq (596/648 genes) and RNAseq (exome capture transcriptome) of tumor specimens and matched blood.

RESULTS

Eighteen male patients (median age 76.5) were enrolled between April 2018 and Dec 2020. At a median follow up of 24.4 months, ORR by RECIST v1.1 was 87%. Metabolic complete response as assessed by PET CT was observed in 8 of 13 (62%) evaluable patients. 6/13 achieved pathological CR post treatment. In two patients, palliative limb amputation was prevented. Median PFS was not reached. The 6mo and 12m PFS rate was 76.5% and 58.8%, respectively. Only four patients (22%) experienced grade 3-4 adverse events. The most frequent genomic alteration was biallelic copy number loss of FOX1A gene. The majority of tumors carried a low TMB, were microsatellite stable (MSS), MMR proficient, did not express PD-L1 and displayed only low lymphocytic infiltrates, rendering them immunologically "cold".

CONCLUSIONS

This prospectively designed phase II study of nivolumab and ipilimumab demonstrates promising activity of this combination in progressive cKS representing a new treatment option in this population.

A Novel Prognostic Ferroptosis-Related lncRNA Signature Associated with Immune Landscape in Invasive Breast Cancer

Breast cancer (BC) represents the most common form of malignant tumors in women. However, the effectiveness of BC immunotherapy remains very low. Ferroptosis is a recently described form of programmed cell death which has unique characteristics, and associated long-chain noncoding RNAs (lncRNA) are thought to influence the occurrence and development of a variety of tumors. We identified 1,636 lncRNAs associated with ferroptosis in BC patients. 299 differentially expressed ferroptosis-related lncRNAs were subjected to univariate, LASSO regression, and multivariate Cox regression analyses to construct a ten ferroptosis-related lncRNA signature. This ten ferroptosis-related lncRNA signature performed very well in predicting survival of BC patients, and the risk score of the mRNA signature was identified as an independent prognostic factor in this cancer entity. In addition, the signature could be used to predict the immune landscape of BC patients. Low-risk patients had enriched immune-related pathways and more infiltration of most types of immune cells. The signature was also associated with the tumor mutation burden in BC. The results have allowed us to assess the potential for immunotherapy targets exposed by this model. The ferroptosis-related lncRNA risk model reported in the current study has clinical utility in BC prognosis and predicted immunotherapy response.

Discordance in Tumor Mutation Burden from Blood and Tissue Affects Association with Response to Immune Checkpoint Inhibition in Real-World Settings

BACKGROUND

Tumor mutation burden (TMB), a biomarker for immune checkpoint inhibitor (CPI) response, is reported by both blood- and tissue-based next-generation sequencing (NGS) vendors. However, the agreement between TMB from blood (bTMB) and tissue (tTMB) in real-world settings, both in absolute value and association with CPI response, is not known.

MATERIALS AND METHODS

This study utilizes Sarah Cannon's precision medicine platform, Genospace, to harmonize clinico-genomic data from 17 206 patients with cancer with NGS results from September 2015 to August 2021. A subset of patients have both bTMB and tTMB results. Statistical analyses are performed in R and include (1) correlation (r) and concordance (ρ) between patient-matched bTMB-tTMB pairs, (2) distribution of total bTMB and tTMB values, and (3) association of bTMB and tTMB with time to CPI therapy failure.

RESULTS

In 410 patient-matched bTMB-tTMB pairs, the median bTMB (m = 10.5 mut/Mb) was significantly higher than the median tTMB (m = 6.0 mut/Mb, P < .001) leading to conflicting "high" and "low" statuses in over one-third of cases at a threshold of 10 mut/Mb (n = 410). Significant differences were observed in the distribution of bTMB values from blood-NGS vendors, with guardant health (GH) reporting higher (m = 10.5 mut/Mb, n = 2183) than Foundation Medicine (FMI, m = 3.8 mut/Mb, n = 462, P < .001). bTMB from GH required a higher threshold (≥40 mut/Mb) than bTMB from FMI (≥12 mut/Mb) in order to be associated with CPI response.

CONCLUSIONS

This study uncovers variability in bTMB reporting among commercial NGS platforms, thereby evidencing a need for assay-specific thresholds in identifying patients who may respond to CPI therapy.