Sequential treatment failures in response to BRAF/MEK and immune checkpoint inhibitors mediated by MAP2K2 and B2M mutations in melanoma

Simultaneous CRISPR screening and spatial transcriptomics reveal intracellular, intercellular, and functional transcriptional circuits

Pooled optical screens have enabled the study of cellular interactions, morphology, or dynamics at massive scale, but they have not yet leveraged the power of highly plexed single-cell resolved transcriptomic readouts to inform molecular pathways. Here, we present a combination of imaging spatial transcriptomics with parallel optical detection of in situ amplified guide RNAs (Perturb-FISH). Perturb-FISH recovers intracellular effects that are consistent with single-cell RNA-sequencing-based readouts of perturbation effects (Perturb-seq) in a screen of lipopolysaccharide response in cultured monocytes, and it uncovers intercellular and density-dependent regulation of the innate immune response. Similarly, in three-dimensional xenograft models, Perturb-FISH identifies tumor-immune interactions altered by genetic knockout. When paired with a functional readout in a separate screen of autism spectrum disorder risk genes in human-induced pluripotent stem cell (hIPSC) astrocytes, Perturb-FISH shows common calcium activity phenotypes and their associated genetic interactions and dysregulated molecular pathways. Perturb-FISH is thus a general method for studying the genetic and molecular associations of spatial and functional biology at single-cell resolution.

Transcriptome-level discovery of survival-associated biomarkers and therapy targets in non-small-cell lung cancer

BACKGROUND AND PURPOSE

Survival rate of patients with lung cancer has increased by over 60% in the recent two decades. With longer survival, the identification of genes associated with survival has emerged as an issue of utmost importance to uncover the most promising biomarkers and therapeutic targets.

EXPERIMENTAL APPROACH

An integrated database was set up by combining multiple independent datasets with clinical data and transcriptome-level gene expression measurements. Univariate and multivariate survival analyses were performed to identify genes with higher expression levels linked to shorter survival. The strongest genes were filtered to include only those with known druggability.

KEY RESULTS

The entire database includes 2852 tumour specimens from 17 independent cohorts. Of these, 2227 have overall survival data and 1256 samples have progression-free survival time. The most significant genes associated with survival were MIF, UBC and B2M in lung adenocarcinoma and ANXA2, CSNK2A2 and KRT18 in squamous cell carcinoma. We also aimed to reveal the best druggable targets in non-smokers lung cancer. The three most promising hits in this cohort were MDK, THY1 and PADI2. The established lung cancer cohort was added to the Kaplan-Meier plotter (https://www.kmplot.com) enabling the validation of future gene expression-based biomarkers in both the present and yet unexamined subgroups of patients.

CONCLUSIONS AND IMPLICATIONS

In this study, we established a comprehensive database of transcriptome-level data for lung cancer. The database can be utilized to identify and rank the most promising biomarkers and therapeutic targets for different subtypes of lung cancer.

Response to Immune Checkpoint Inhibitors Is Affected by Deregulations in the Antigen Presentation Machinery: A Systematic Review and Meta-Analysis

Immune checkpoint inhibitors (ICI) targeting programmed death 1 (PD-1), its ligand (PD-L1), or cytotoxic T-lymphocyte antigen 4 (CTLA-4) have shown promising results against multiple cancers, where they reactivate exhausted T cells primed to eliminate tumor cells. ICI therapies have been particularly successful in hypermutated cancers infiltrated with lymphocytes. However, resistance may appear in tumors evading the immune system through alternative mechanisms than the PD-1/PD-L1 or CTLA-4 pathways. A systematic pan-cancer literature search was conducted to examine the association between alternative immune evasion mechanisms via the antigen presentation machinery (APM) and resistance towards ICI treatments targeting PD-1 (pembrolizumab and nivolumab), PD-L1 (durvalumab, avelumab, and atezolizumab), and CTLA-4 (ipilimumab). The APM proteins included the human leucocyte antigen (HLA) class I, its subunit beta-2 microglobulin (B2M), the transporter associated with antigen processing (TAP) 1, TAP2, and the NOD-like receptor family CARD domain containing 5 (NLRC5). In total, 18 cohort studies (including 21 original study cohorts) containing 966 eligible patients and 9 case studies including 12 patients were reviewed. Defects in the APM significantly predicted poor clinical benefit with an odds ratio (OR) of 0.39 (95% CI 0.24−0.63, p < 0.001). The effect was non-significant, when considering complete and partial responses only (OR = 0.52, 95% CI 0.18−1.47, p = 0.216). In summary, the APM contains important targets for tumorigenic alterations which may explain insensitivity towards ICI therapy.

The immune-related role of beta-2-microglobulin in melanoma

Despite the remarkable success of immunotherapy in the treatment of melanoma, resistance to these agents still affects patient prognosis and response to therapies. Beta-2-microglobulin (β2M), an important subunit of major histocompatibility complex (MHC) class I, has important biological functions and roles in tumor immunity. In recent years, increasing studies have shown that B2M gene deficiency can inhibit MHC class I antigen presentation and lead to cancer immune evasion by affecting β2M expression. Based on this, B2M gene defect and T cell-based immunotherapy can interact to affect the efficacy of melanoma treatment. Taking into account the many recent advances in B2M-related melanoma immunity, here we discuss the immune function of the B2M gene in tumors, its common genetic alteration in melanoma, and its impact on and related improvements in melanoma immunotherapy. Our comprehensive review of β2M biology and its role in tumor immunotherapy contributes to understanding the potential of B2M gene as a promising melanoma therapeutic target.

B2M gene expression shapes the immune landscape of lung adenocarcinoma and determines the response to immunotherapy

Loss of the B2M gene is associated with tumour immune escape and resistance to immunotherapy. However, genetic alterations of the B2M gene are rare. We performed an integrative analysis of the mutational and transcriptional profiles of large cohorts of non-small-cell lung cancer (NSCLC) patients and found that epigenetic downregulation of B2M is common. B2M-low tumours exhibit a suppressive immune microenvironment characterized by reduced infiltration of immune cells of various lineages; in B2M-high tumours, more T and natural killer cells are present, but their activities are constrained by immune checkpoint molecules, indicating the diverse mechanisms of immune evasion. High levels of B2M mRNA, but not PD-L1, are correlated with an enhanced response to PD-1-based immunotherapy, suggesting its value for immunotherapy response prediction in solid tumours. Notably, a high tumour mutation burden (TMB) is associated with low B2M expression, which may explain the poor predictive value of the TMB in some situations. In syngeneic mouse models, genetic ablation of B2M in tumour cells causes resistance to PD-1-based immunotherapy, and B2M knockdown also diminishes the therapeutic efficacy. Moreover, forced expression of B2M in tumour models improves the response to immunotherapy, suggesting that B2M levels have significant impacts on treatment outcomes. Finally, we provide insight into the roles of transcription factors and KRAS mutations in B2M expression and the anticancer immune response. In conclusion, genetic and epigenetic regulation of B2M fundamentally shapes the NSCLC immune microenvironment and may determine the response to checkpoint blockade-based immunotherapy.

Resistance to Molecularly Targeted Therapies in Melanoma

Malignant melanoma is the most aggressive type of skin cancer with invasive growth patterns. In 2021, 106,110 patients are projected to be diagnosed with melanoma, out of which 7180 are expected to die. Traditional methods like surgery, radiation therapy, and chemotherapy are not effective in the treatment of metastatic and advanced melanoma. Recent approaches to treat melanoma have focused on biomarkers that play significant roles in cell growth, proliferation, migration, and survival. Several FDA-approved molecular targeted therapies such as tyrosine kinase inhibitors (TKIs) have been developed against genetic biomarkers whose overexpression is implicated in tumorigenesis. The use of targeted therapies as an alternative or supplement to immunotherapy has revolutionized the management of metastatic melanoma. Although this treatment strategy is more efficacious and less toxic in comparison to traditional therapies, targeted therapies are less effective after prolonged treatment due to acquired resistance caused by mutations and activation of alternative mechanisms in melanoma tumors. Recent studies focus on understanding the mechanisms of acquired resistance to these current therapies. Further research is needed for the development of better approaches to improve prognosis in melanoma patients. In this article, various melanoma biomarkers including BRAF, MEK, RAS, c-KIT, VEGFR, c-MET and PI3K are described, and their potential mechanisms for drug resistance are discussed.

Development and External Validation of a Novel Immune Checkpoint-Related Gene Signature for Prediction of Overall Survival in Hepatocellular Carcinoma

Objective: The purpose of this study was to develop and validate a novel immune checkpoint-related gene signature for prediction of overall survival (OS) in hepatocellular carcinoma (HCC). Methods: mRNA expression profiles and clinical follow-up information were obtained in the International Cancer Genome Consortium database. An external dataset from The Cancer Genome Atlas (TCGA) Liver Hepatocellular Carcinoma database was used to validate the results. The univariate and multivariate Cox regression analyses were performed based on the differentially expressed genes. We generated a four-mRNA signature to predict patient survival. Furthermore, the reliability and validity were validated in TCGA cohort. An integrated bioinformatics approach was performed to evaluate its diagnostic and prognostic value. Results: A four-gene (epidermal growth factor, mutated in colorectal cancer, mitogen-activated protein kinase kinase 2, and NRAS proto-oncogene, GTPase) signature was built to classify patients into two risk groups using a risk score with different OS in two cohorts (all P < 0.0001). Multivariate regression analysis demonstrated the signature was an independent predictor of HCC. Furthermore, the signature presented an excellent diagnostic power in differentiating HCC and adjacent tissues. Immune cell infiltration analysis revealed that the signature was associated with a number of immune cell subtypes. Conclusion: We identified a four-immune checkpoint-related gene signature as a robust biomarker with great potential for clinical application in risk stratification and OS prediction in HCC patients and could be a potential indicator of immunotherapy in HCC. The diagnostic signature had been validated to accurately distinguish HCC from adjacent tissues.