Increase in antibody-dependent cellular cytotoxicity (ADCC) in a patient with advanced colorectal carcinoma carrying a KRAS mutation under lenalidomide therapy

NK Cell-Targeted Immunotherapies in Bladder Cancer: Beyond Checkpoint Inhibitors

BACKGROUND

For decades, immunotherapies have been integral for the treatment and management of bladder cancer, with immune checkpoint inhibitors (ICIs) transforming patient care in recent years. However, response rates are poor to T cell-targeted ICIs such as programmed cell death protein 1 (PD-1) and programmed cell death-ligand 1 (PD-L1) blocking antibodies, framing a critical need for complementary immunotherapies. Promising strategies involve harnessing the activation potential of natural killer (NK) cells. They quickly exert their antitumor activity via signaling through germline-encoded activating receptors and are rapidly sensitized to new tissue microenvironments via their regulation by polymorphic HLA class I, KIR and NKG2A receptors.

OBJECTIVE

In this review, we examined the roles of currently available NK-targeted antitumor treatment strategies such as engineered viral vectors, small-molecule IMiDs, NK agonist antibodies, interleukins, and chimeric antigen receptor (CAR) NK cells, and their potential for improving the efficacy of immunotherapy in the treatment of bladder cancer.

METHODS

Through review of current literature, we summarized our knowledge of NK cells in solid tumors and hematologic malignancies as their roles pertain to novel immunotherapies already being applied to the treatment of bladder cancer or that offer rationale for considering as potential novel immunotherapeutic strategies.

RESULTS

NK cells play a critical role in shaping the tumor microenvironment (TME) that can be exploited to improve T cell-targeted immunotherapies.

CONCLUSIONS

Emerging evidence suggests that NK cells are a prime target for improving antitumor functions in immunotherapies for the treatment of bladder cancer. Further research into profiling NK cells in settings of immunotherapies for bladder cancer could help identify patients who might maximally benefit from NK cell-targeted immunotherapies and the various approaches for exploiting their antitumor properties.

The Right Partner in Crime: Unlocking the Potential of the Anti-EGFR Antibody Cetuximab via Combination With Natural Killer Cell Chartering Immunotherapeutic Strategies

Cetuximab has an established role in the treatment of patients with recurrent/metastatic colorectal cancer and head and neck squamous cell cancer (HNSCC). However, the long-term effectiveness of cetuximab has been limited by the development of acquired resistance, leading to tumor relapse. By contrast, immunotherapies can elicit long-term tumor regression, but the overall response rates are much more limited. In addition to epidermal growth factor (EGFR) inhibition, cetuximab can activate natural killer (NK) cells to induce antibody-dependent cellular cytotoxicity (ADCC). In view of the above, there is an unmet need for the majority of patients that are treated with both monotherapy cetuximab and immunotherapy. Accumulated evidence from (pre-)clinical studies suggests that targeted therapies can have synergistic antitumor effects through combination with immunotherapy. However, further optimizations, aimed towards illuminating the multifaceted interplay, are required to avoid toxicity and to achieve better therapeutic effectiveness. The current review summarizes existing (pre-)clinical evidence to provide a rationale supporting the use of combined cetuximab and immunotherapy approaches in patients with different types of cancer.

Predicting the Survival and Immune Landscape of Colorectal Cancer Patients Using an Immune-Related lncRNA Pair Model

Background

Accumulating evidence has demonstrated that immune-related long non-coding ribonucleic acids (irlncRNAs) can be used as prognostic indicators of overall survival (OS) in patients with colorectal cancer (CRC). Our aim in this research, therefore, was to construct a risk model using irlncRNA pairs with no requirement for a specific expression level, in hope of reliably predicting the prognosis and immune landscape of CRC patients.

Methods

Clinical and transcriptome profiling data of CRC patients downloaded from the Cancer Genome Atlas (TCGA) database were analyzed to identify differentially expressed (DE) irlncRNAs. The irlncRNA pairs significantly correlated with the prognosis of patients were screened out by univariable Cox regression analysis and a prognostic model was constructed by Lasso and multivariate Cox regression analyses. A receiver operating characteristic (ROC) curve was then plotted, with the area under the curve calculated to confirm the reliability of the model. Based on the optimal cutoff value, CRC patients in the high- or low-risk groups were distinguished, laying the ground for evaluating the risk model from the following perspectives: survival, clinicopathological traits, tumor-infiltrating immune cells (TIICs), antitumor drug efficacy, kinase inhibitor efficacy, and molecules related to immune checkpoints.

Results

A prognostic model consisting of 15 irlncRNA pairs was constructed, which was found to have a high correlation with patient prognosis in a cohort from the TCGA (p < 0.001, HR = 1.089, 95% CI [1.067-1.112]). According to both univariate and multivariate Cox analyses, this model could be used as an independent prognostic indicator in the TCGA cohort (p < 0.001). Effective differentiation between high- and low-risk patients was also accomplished, on the basis of aggressive clinicopathological characteristics, sensitivity to antitumor drugs, and kinase inhibitors, the tumor immune infiltration status, and the expression levels of specific molecules related to immune checkpoints.

Conclusion

The prognostic model established with irlncRNA pairs is a promising indicator for prognosis prediction in CRC patients.

Chemotherapy agents stimulate dendritic cells against human colon cancer cells through upregulation of the transporter associated with antigen processing

Single immunotherapy fails to demonstrate efficacy in patients with microsatellite stable (MSS) metastatic colorectal cancer (mCRC). Research on immune reactions before and after systemic agents for mCRC is warranted. Our study examined cell line models to compare the expression of immune surface markers on colon cancer cells before and after chemotherapy agents. We also elucidated mechanisms underlying the effects of chemotherapy agents on immune surface markers. We used real-world clinical samples with NanoString analysis and the Perkin-Elmer Opal multiplex system. We established that chemotherapy agents, particularly 7-ethyl-10-hydroxycamptothecin (SN-38), the active metabolite of irinotecan, stimulated the expression of stimulatory MHC class I alleles through stimulation the pathway of transporters associated with antigen processing 1 and 2 (TAP1 and TAP2) in cell line models. Application of infected cell protein 47 (ICP-47), a specific inhibitor of the TAP1/TAP2, significantly inhibited expression of TAP1/TAP2 and also inhibited the expression of the downstream MHC class I. In the functional assay, SN-38 significantly promoted the phagocytosis of colon cancer cells by monocyte-derived dendritic cells (MoDCs). We confirmed that the expression of major histocompatibility complex (MHC) class I, significantly increased after first-line chemotherapy and targeted therapy in the samples of real-world patients with de novo mCRC. Our study provides new insights for novel immunotherapy combinations.

How to Hit Mesenchymal Stromal Cells and Make the Tumor Microenvironment Immunostimulant Rather Than Immunosuppressive

Experimental evidence indicates that mesenchymal stromal cells (MSCs) may regulate tumor microenvironment (TME). It is conceivable that the interaction with MSC can influence neoplastic cell functional behavior, remodeling TME and generating a tumor cell niche that supports tissue neovascularization, tumor invasion and metastasization. In addition, MSC can release transforming growth factor-beta that is involved in the epithelial-mesenchymal transition of carcinoma cells; this transition is essential to give rise to aggressive tumor cells and favor cancer progression. Also, MSC can both affect the anti-tumor immune response and limit drug availability surrounding tumor cells, thus creating a sort of barrier. This mechanism, in principle, should limit tumor expansion but, on the contrary, often leads to the impairment of the immune system-mediated recognition of tumor cells. Furthermore, the cross-talk between MSC and anti-tumor lymphocytes of the innate and adaptive arms of the immune system strongly drives TME to become immunosuppressive. Indeed, MSC can trigger the generation of several types of regulatory cells which block immune response and eventually impair the elimination of tumor cells. Based on these considerations, it should be possible to favor the anti-tumor immune response acting on TME. First, we will review the molecular mechanisms involved in MSC-mediated regulation of immune response. Second, we will focus on the experimental data supporting that it is possible to convert TME from immunosuppressive to immunostimulant, specifically targeting MSC.

Rationale for combination of therapeutic antibodies targeting tumor cells and immune checkpoint receptors: Harnessing innate and adaptive immunity through IgG1 isotype immune effector stimulation

Immunoglobulin (Ig) G1 antibodies stimulate antibody-dependent cell-mediated cytotoxicity (ADCC). Cetuximab, an IgG1 isotype monoclonal antibody, is a standard-of-care treatment for locally advanced and recurrent and/or metastatic squamous cell carcinoma of the head and neck (SCCHN) and metastatic colorectal cancer (CRC). Here we review evidence regarding the clinical relevance of cetuximab-mediated ADCC and other immune functions and provide a biological rationale concerning why this property positions cetuximab as an ideal partner for immune checkpoint inhibitors (ICIs) and other emerging immunotherapies. We performed a nonsystematic review of available preclinical and clinical data involving cetuximab-mediated immune activity and combination approaches of cetuximab with other immunotherapies, including ICIs, in SCCHN and CRC. Indeed, cetuximab mediates ADCC activity in the intratumoral space and primes adaptive and innate cellular immunity. However, counterregulatory mechanisms may lead to immunosuppressive feedback loops. Accordingly, there is a strong rationale for combining ICIs with cetuximab for the treatment of advanced tumors, as targeting CTLA-4, PD-1, and PD-L1 can ostensibly overcome these immunosuppressive counter-mechanisms in the tumor microenvironment. Moreover, combining ICIs (or other immunotherapies) with cetuximab is a promising strategy for boosting immune response and enhancing response rates and durability of response. Cetuximab immune activity–including, but not limited to, ADCC–provides a strong rationale for its combination with ICIs or other immunotherapies to synergistically and fully mobilize the adaptive and innate immunity against tumor cells. Ongoing prospective studies will evaluate the clinical effect of these combination regimens and their immune effect in CRC and SCCHN and in other indications.

An Optimal Mean Based Block Robust Feature Extraction Method to Identify Colorectal Cancer Genes with Integrated Data

It is urgent to diagnose colorectal cancer in the early stage. Some feature genes which are important to colorectal cancer development have been identified. However, for the early stage of colorectal cancer, less is known about the identity of specific cancer genes that are associated with advanced clinical stage. In this paper, we conducted a feature extraction method named Optimal Mean based Block Robust Feature Extraction method (OMBRFE) to identify feature genes associated with advanced colorectal cancer in clinical stage by using the integrated colorectal cancer data. Firstly, based on the optimal mean and L _2,1-norm, a novel feature extraction method called Optimal Mean based Robust Feature Extraction method (OMRFE) is proposed to identify feature genes. Then the OMBRFE method which introduces the block ideology into OMRFE method is put forward to process the colorectal cancer integrated data which includes multiple genomic data: copy number alterations, somatic mutations, methylation expression alteration, as well as gene expression changes. Experimental results demonstrate that the OMBRFE is more effective than previous methods in identifying the feature genes. Moreover, genes identified by OMBRFE are verified to be closely associated with advanced colorectal cancer in clinical stage.