Beyond Tumor Mutation Burden: Tumor Neoantigen Burden as a Biomarker for Immunotherapy and Other Types of Therapy

High resolution clonal architecture of hypomutated Wilms tumours

A paradigm of childhood cancers is that they have a low mutation burden, with some ostensibly bearing fewer mutations than the normal tissues from which they derive. We set out to resolve this paradox by examining paediatric renal cancers with exceptionally few mutations using high resolution, high depth sequencing approaches. We find that apparent hypomutation is the result of unusual clonal architecture due to a normal tissue-like mode of tumour evolution, raising the possibility that the mutation burden of some cancers has been systematically misjudged.

Deficient Mismatch Repair and Microsatellite Instability in Solid Tumors

The integrity of the genome is maintained by mismatch repair (MMR) proteins that recognize and repair base mismatches and insertion/deletion errors generated during DNA replication and recombination. A defective MMR system results in genome-wide instability and the progressive accumulation of mutations. Tumors exhibiting deficient MMR (dMMR) and/or high levels of microsatellite instability (termed "microsatellite instability high", or MSI-H) have been shown to possess fundamental differences in clinical, pathological, and molecular characteristics, distinguishing them from their "microsatellite stable" (MSS) counterparts. Molecularly, they are defined by a high mutational burden, genetic instability, and a distinctive immune profile. Their distinct genetic and immunological profiles have made dMMR/MSI-H tumors particularly amenable to treatment with immune checkpoint inhibitors (ICIs). The ongoing development of biomarker-driven therapies and the evaluation of novel combinations of immune-based therapies, with or without the use of conventional cytotoxic treatment regimens, continue to refine treatment strategies with the goals of maximizing therapeutic efficacy and survival outcomes in this distinct patient population. Moreover, the resultant knowledge of the mechanisms by which these features are suspected to render these tumors more responsive, overall, to immunotherapy may provide information regarding the potential optimization of this therapeutic approach in tumors with proficient MMR (pMMR)/MSS tumors.

GIMAP8 could serve as a potential prognostic factor for lung adenocarcinoma and is closely related to immunity

GTPase IMAP family member 8 (GIMAP8) plays a key role in pathophysiology of several malignancies. The objective of this current research endeavor was to investigate the prognosis value of GIMAP8 in lung adenocarcinoma and examine how it relates to immunity. Expression profiles associated with GIMAP8 and related clinical details were acquired from The Cancer Genome Atlas database, and we conducted survival analysis, enrichment analysis and immune infiltration studies. Additionally, we evaluated the effect of GIMAP8 on radiation resistance of tumor by in vivo and in vitro experiments. Our results showed that lung adenocarcinoma tumor tissues exhibited lower GIMAP8 levels compared to nearby normal tissues. Furthermore, decreased GIMAP8 expression strongly correlated with poorer OS. The expression of GIMAP8 is closely related to the formation of radiation resistance in tumor cells. GSEA identified multiple signaling pathways linked to GIMAP8, including immune-related, chemokine, cell adhesion molecule, and NF-κB signaling pathways. GIMAP8 expression strongly correlated with the expression of immune checkpoint molecules, tumor mutational burden, tumor neoantigen burden, immune cells, and tumor immune microenvironment. GIMAP8 was found to have an inhibitory effect on lung adenocarcinoma and was closely related to the immune response. Moreover, GIMAP8 may also influence radiation resistance in tumors.

Construction of ubiquitination-related risk model for predicting prognosis in lung adenocarcinoma

Lung adenocarcinoma is the most prevalent lung cancer type. Ubiquitination, a critical post-translational modification process that regulates protein degradation and signaling pathways, has been implicated in various cancers, including LUAD. We aimed to explore the associations between ubiquitination and lung adenocarcinoma. TCGA-LUAD cohort served as the training set. Unsupervised clustering, univariate Cox regression, Random Survival Forests, and least absolute shrinkage and selection operator (LASSO) Cox regression were applied to identify ubiquitination-related genes (URGs), then ubiquitination-related risk scores (URRS) were calculated using gene expression and the univariate Cox's coefficient. Comparisons between the high and the low URRS group regarding chemotherapy drug response, immune infiltration level, tumor mutation burden (TMB), tumor neoantigen load (TNB), PD1/L1 expression, and enriched pathways were performed. URRS was calculated based on the expression of DTL, UBE2S, CISH, and STC1. Patients with higher URRS had a worse prognosis (Hazard Ratio [HR] = 0.54, 95% Confidence Interval [CI]: 0.39-0.73, p < 0.001), and the prognosis of the URRS was further confirmed in 6 external validation cohorts (Hazard Ratio [HR] = 0.58, 95% Confidence Interval [CI]: 0.36-0.93, pmax = 0.023). The high URRS group had higher PD1/L1 expression level (p < 0.05), TMB (p < 0.001), TNB (p < 0.001), and TME scores (p < 0.001). The IC50 values of various chemotherapy drugs were lower in the high URRS group. In addition, we found that upregulation of STC1, UBE2S, and DTL was associated with worse, while upregulation of CISH was associated with better prognosis. We also performed a reverse transcription-quantitative polymerase chain reaction (RT-qPCR) for validation. In conclusion, the ubiquitination-based signature might serve as a biomarker to help evaluate the prognosis, biological features, and appropriate treatment for patients with lung adenocarcinoma.

Lessons learned from a decade of immune checkpoint inhibition: The good, the bad, and the ugly

Discovering the brakes/checkpoints that cancer places on the immune system to prevent being eradicated led to the 2018 Nobel Prize and the development of multiple Food and Drug Administration-approved immune checkpoint inhibitors (ICIs). ICIs have transformed the treatment of numerous cancer types and, remarkably, some patients with end-stage metastatic disease can achieve durable, complete remissions - cures. Still, ICIs cause significant immune-related toxicities, and most tumors are resistant. Unusual progression patterns such as pseudo-progression and hyper-progression (accelerated progression) can occur. Biomarkers for ICI response/resistance include microsatellite instability, high tumor mutational burden, and PD-L1 immunohistochemistry positivity; but they are imperfect, perhaps because of immune system complexity. Herein, we explore the good, the bad, and the ugly of ICIs in cancer treatment.

Analysis of Multiple Programmed Cell Death Patterns and Functional Validations of Apoptosis-Associated Genes in Lung Adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is marked by its considerable aggressiveness and pronounced heterogeneity. Programmed cell death (PCD) plays a pivotal role in the progression of tumors, their aggressive behavior, resistance to treatment, and recurrence of the disease.

PATIENTS AND METHODS

Using expression data from 878 patients across four multicenter cohorts, we identified 13 consensus prognostic genes from 1481 genes associated with PCD. We employed 10 machine-learning algorithms, generating 101 combinations, from which the optimal algorithm was chosen to develop an artificial intelligence-derived cell death index (CDI) on the basis of the average C-index.

RESULTS

The training cohort and three external validation cohorts consistently demonstrated that CDI could accurately predict LUAD prognosis. Moreover, CDI showed significantly greater accuracy than traditional clinical variables, molecular characteristics, and 22 previously published signatures. Patients in the low-CDI group had a more favorable prognosis, higher levels of immune cell infiltration, better responsiveness to immunotherapy, and a higher likelihood of displaying the "hot tumor" phenotype. Single-cell analysis revealed that neutrophils had the highest CDI scores and exhibited significant differences in marker gene expression.

CONCLUSIONS

Pseudotime trajectory analysis indicated that BCL2L14 plays a crucial role in the developmental pathway of neutrophils, potentially influencing the fate of LUAD cells. Knockdown of BCL2L14 significantly reduced the growth, proliferation, and colony formation abilities of LUAD cells, while also enhancing apoptosis rates.

Overview on biomarkers for immune oncology drugs

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

Advances in Immunotherapy in Hepatocellular Carcinoma

Over the past several years, the therapeutic landscape for patients with advanced, unresectable, or metastatic hepatocellular carcinoma has been transformed by the incorporation of checkpoint inhibitor immunotherapy into the treatment paradigm. Frontline systemic treatment options have expanded beyond anti-angiogenic tyrosine kinase inhibitors, such as sorafenib, to a combination of immunotherapy approaches, including atezolizumab plus bevacizumab and durvalumab plus tremelimumab, both of which have demonstrated superior response and survival to sorafenib. Additionally, combination treatments with checkpoint inhibitors and tyrosine kinase inhibitors have been investigated with variable success. In this review, we discuss these advances in systemic treatment with immunotherapy, with a focus on understanding both the underlying biology and mechanism of these strategies and their efficacy outcomes in clinical trials. We also review challenges in identifying predictive biomarkers of treatments and discuss future directions with novel immunotherapy targets.

Multi-omics analysis reveals lysosome-associated molecular subtype characterization and prognostic modeling system in lung adenocarcinoma

Background: Lung adenocarcinoma (LUAD) poses a significant challenge in current treatments due to its high recurrence and metastasis rates. Despite preliminary evidence suggesting the role of lysosomes in LUAD, it remains unclear whether lysosome-related functions can be effectively used for risk stratification of LUAD patients and involved lysosome-related functional targets are still needed to be explored. Method: An integrated analysis of TCGA and GEO databases was conducted to explore the potential role of lysosome-related genes (LRGs) in LUAD. Unsupervised consensus clustering analysis was utilized to explore the LRG molecular subtypes in LUAD. ESTIMATE and ssGSEA algorithms were performed to evaluate the immune infiltration characterization of LUAD samples. LASSO-univariate and multivariate Cox analysis were used to construct the LRG score model. Single-cell sequencing analysis was performed to reveal the distribution characteristics in different cell subpopulations of selected LRGs. In vitro experiments including western blotting, PCR, colony formation assays, and Transwell assays were used to verify the expression and biological functions of the selected target in LUAD. Results: Through multi-omics integration analysis algorithms, we successfully developed a prognostic risk stratification system based on LRG scoring in LUAD and constructed a nomogram diagnostic model. Various bioinformatics analyses indicated the potential clinical value of the LRG scoring system. Single-cell sequencing analysis further revealed the composition of cell subpopulations and the expression characteristics of prognostic signatures. SLC2A1, one of the selected targets, was validated through in vitro experiments to regulate the proliferation and migration of LUAD cells, thereby confirming the reliability of the bioinformatics results. Conclusion: Our results demonstrate that effective risk stratification of LUAD patients can be achieved through LRGs by multi-omics analysis integration. Furthermore, we validated key prognostic targets in vitro, providing new ideas for future clinical treatment.

A comprehensive pan-cancer analysis of RNF187 in human tumors

PURPOSE

RING Finger 187 (RNF187) has recently emerged as a potential contributor to tumorigenesis. However, a comprehensive pan-cancer analysis of RNF187 in human tumors has not been undertaken until now.

METHODS

Our study aims to investigate RNF187 expression across 33 different types of human tumors, utilizing data from the TCGA and GTEx databases.

RESULTS

The pan-cancer analysis revealed significant upregulation of RNF187 in 27 types of cancers, contrasting with only low expression in LAML, with no statistical differences in OV and SARC. Notably, discernible associations were identified between RNF187 expression and the prognosis of cancer patients. Our investigation also unveiled correlations between RNA modification of RNF187 across various cancer types. Further exploration indicated a positive correlation between RNF187 levels and the presence of cancer-associated fibroblasts (CAFs) in numerous tumor types. Additionally, RNF187 exhibited correlations with a majority of immune inhibitory and stimulatory genes, as well as chemokines, receptors, MHC molecules, immunoinhibitors, and immunostimulators in various cancers. The findings highlighted associations between RNF187 expression and Tumor Mutational Burden (TMB), Microsatellite Instability (MSI) and Homologous Recombination Deficiency (HRD) in specific tumors. Finally, RNF187 showed a significant positive association with five genes (ALKBH4, FAM134A, MLST8, SANP47 and TMEM9) across the majority of tumors. GO enrichment and KEGG pathway analyses suggested that RNF187 may play a role in the pathogenesis of cancer through processes such as "bounding membrane of organelle," "macroautophagy," "proton-transporting V-type ATPase complex," "autophagy," "Ubiquitin mediated proteolysis," "Ferroptosis," "Phagosome," and etc. CONCLUSION: Our inaugural pan-cancer study aims to provide a profound understanding of RNF187 in tumorigenesis across diverse types of tumors.

Non-Genetic Biomarkers in Merkel Cell Carcinoma: Prognostic Implications and Predictive Utility for Response to Anti-PD-(L)1 Immune Checkpoint Inhibitors

Merkel cell carcinoma (MCC) is a skin cancer that arises due to either Merkel cell polyomavirus infection (MCPyV) or ultraviolet (UV) radiation exposure, presenting primarily in the head and neck region of fair-skinned males. The recent success of PD-(L)1 immune checkpoint inhibitors (ICIs) in locally advanced/metastatic MCC, with an objective response rate (ORR) around 50% and improved survival, as a first-line treatment has moved ICIs to the forefront of therapy for MCC and generated interest in identifying biomarkers to predict clinical response. The MCC tumour microenvironment (TME) contains various components of the adaptive and innate immune system. These components can contribute to tumour immune escape through immunosuppression by preventing entrance of other immune cells or by aiding in the cytotoxic clearance of tumour cells. We aim to combine information from studies of baseline and on-treatment monitoring of the TME to help predict the success of ICIs in MCC. This review enhances the understanding of how CD8 T cells, γδ T cells and macrophages may impact predictions of response rates to ICIs in MCC patients. These immune cells are non-genetic biomarkers that can also be used to determine prognosis in MCC treatment.

Advancements in immunotherapy for colorectal cancer treatment: a comprehensive review of strategies, challenges, and future prospective

PURPOSE

Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide. Metastatic colorectal cancer (mCRC) continues to present significant challenges, particularly in patients with proficient mismatch repair/microsatellite stable (pMMR/MSS) tumors. This narrative review aims to provide recent developments in immunotherapy for CRC treatment, focusing on its efficacy and challenges.

METHODS

This review discussed the various immunotherapeutic strategies for CRC treatment, including immune checkpoint inhibitors (ICIs) targeting PD-1 and PD-L1, combination therapies involving ICIs with other modalities, chimeric antigen receptor T-cell (CAR-T) cell therapy, and cancer vaccines. The role of the tumor microenvironment and immune evasion mechanisms was also explored to understand their impact on the effectiveness of these therapies.

RESULTS

This review provides a comprehensive update of recent advancements in immunotherapy for CRC, highlighting the potential of various immunotherapeutic approaches, including immune checkpoint inhibitors, combination therapies, CAR-T therapy, and vaccination strategies. The results of checkpoint inhibitors, particularly in patients with MSI-H/dMMR tumors, which have significant improvements in survival rates have been observed. Furthermore, this review also addresses the challenges faced in treating pMMR/MSS CRC, which remains resistant to immunotherapy.

CONCLUSION

Immunotherapy plays a significant role in the treatment of CRC, particularly in patients with MSI-H/dMMR tumors. However, many challenges remain, especially in treating pMMR/MSS CRC. This review discussed the need for further research into combination therapies, biomarker development, CAR-T cell therapy, and a deeper understanding of immune evasion mechanisms for CRC treatment.

In silico neoantigen screening and HLA multimer-based validation identify immunogenic neopeptide in multifocal lung adenocarcinoma

Background

Mutations commonly occur in cancer cells, arising neoantigen as potential targets for personalized immunotherapy of lung adenocarcinoma (LUAD). However, the substantial heterogeneity observed among individuals and distinct foci within the same patient presents significant challenges in formulating immunotherapy strategies. The aim of the work is to characterize the mutation pattern and identify neopeptides across different patients and diverse foci within the same patients with LUAD.

Methods

Seven lung adenocarcinoma samples and matched tissues/blood are collected from 4 patients with LUAD for whole exome sequencing, mutation signature analysis, HLA binding prediction and neoantigen screening. Dimeric HLA-A2 molecules were prepared by Bac-to-Bac baculovirus expression system to establish a T cell stimulation system based on HLA-A2-coated artificial antigen-presenting cells for the validation of immunogenic neopeptides.

Results

Similar mutation pattern with predominant missense mutation and high tumor mutation burden was observed across individuals with lung adenocarcinomas and between non-invasive and invasive foci. We screened and identified 3 consistent mutated genes among 100 top genes with highest mutation scores contributed across 4 patients, and 3 mutated peptides among 30 with highest HLA-A2 binding affinity distributed in at least 2 out of 4 foci in the same patient. Notably, LUAD-7-MT peptide encoded by NANOGNB demonstrated higher immunogenicity in promoting CD8+ T cells proliferation and IFN-γ secretion than the corresponding wildtype peptide.

Conclusions

This study provides an in-depth analysis of mutation characteristics of LUAD and establishes a neoantigen screening and validation system for identifying immunogenicity neopeptide across individual patients and diverse foci in the same patient with multifocal LUAD.

Genomic and transcriptomic analyses identify distinctive features of triple-negative inflammatory breast cancer

Triple-negative inflammatory breast cancer (TN-IBC) is the most aggressive type of breast cancer, yet its defining genomic, molecular, and immunological features remain largely unknown. In this study, we performed the largest and most comprehensive genomic and transcriptomic analyses of prospectively collected TN-IBC patient samples from a phase II clinical trial (ClinicalTrials.gov, NCT02876107, registered on August 22, 2016) and compared them to similarly analyzed stage III TN-non-IBC patient samples (ClinicalTrials.gov, NCT02276443, registered on October 21, 2014). We found that TN-IBC tumors have distinctive genomic, molecular, and immunological characteristics, including a lower tumor mutation load than TN-non-IBC, and an association of immunosuppressive tumor-infiltrating immune components with an unfavorable response to neoadjuvant chemotherapy. To our knowledge, this is the only study in which TN-IBC and TN-non-IBC samples were collected prospectively. Our analysis improves the understanding of the molecular landscape of the most aggressive subtype of breast cancer. Further studies are needed to discover novel prognostic biomarkers and druggable targets for TN-IBC.

Machine learning-driven estimation of mutational burden highlights DNAH5 as a prognostic marker in colorectal cancer

BACKGROUND

Tumor Mutational Burden (TMB) have emerged as pivotal predictive biomarkers in determining prognosis and response to immunotherapy in colorectal cancer (CRC) patients. While Whole Exome Sequencing (WES) stands as the gold standard for TMB assessment, carry substantial costs and demand considerable time commitments. Additionally, the heterogeneity among high-TMB patients remains poorly characterized.

METHODS

We employed eight advanced machine learning algorithms to develop gene-panel-based models for TMB estimation. To rigorously compare and validate these TMB estimation models, four external cohorts, involving 1,956 patients, were used. Furthermore, we computed the Pearson correlation coefficient between the estimated TMB and tumor neoantigen levels to elucidate their association. CD8+ tumor-infiltrating lymphocyte (TIL) density was assessed via immunohistochemistry.

RESULTS

The TMB estimation model based on the Lasso algorithm, incorporating 20 genes, exhibiting satisfactory performance across multiple independent cohorts (R2 ≥ 0.859). This 20-gene TMB model proved to be an independent prognostic indicator for the progression-free survival (PFS) of CRC patients (p = 0.001). DNAH5 mutations were associated with a more favorable prognosis in high-TMB CRC patients, and correlated strongly with tumor neoantigen levels and CD8+ TIL density.

CONCLUSIONS

The 20-gene model offers a cost-efficient approach to precisely estimating TMB, providing prognosis in patients with CRC. Incorporating DNAH5 within this model further refines the categorization of patients with elevated TMB. Utilizing the 20-gene model facilitates the stratification of patients with CRC, enabling more precise treatment planning.

Prognostic and immunological values of SKA3 for overall survival in lung adenocarcinoma and its RNA binding protein involved mechanisms

This article aimed to investigate the correlations among SKA3 expression and prognosis, clinical relevance, tumor immunity, and RNA-binding protein (RBP)-involved mechanisms for overall survival (OS) in lung adenocarcinoma (LUAD). To explore the SKA3 expression level in LUAD by analyzing the genomic data as well as related clinical characteristics from the database of TCGA. Nomogram and gene set enrichment analysis (GSEA) were applied, respectively, to evaluate the performance of SKA3 in LUAD. Correlations between SKA3 and immunity and RBP-involved mechanisms were also performed. SKA3 had a higher expression level in LUAD samples than in adjacent normal lung samples, with shorter survival times in the high-SKA3-expressed LUAD subgroup (P < 0.05). qRT-PCR results remained consistent (P < 0.05). Uni-/multivariate Cox analyses revealed that SKA3 could have independent prognostic ability for LUAD (both P < 0.05). The nomogram model constructed with clinical pathological parameters and SKA3 expression levels predicted OS rates for LUAD and GSEA revealed SKA3-related pathways. In aspects of tumor immunity, SKA3 was significantly involved with tumor neoantigen burden, tumor mutational burden, immune cell pathways, and immune checkpoint inhibitor (ICI) molecules (all P < 0.05). The CellMiner database also found significant correlations between SKA3 and the antitumor drug sensitivity of chemotherapy, fenretinide, and PX-316. Besides, a total of nine LncRNA/RBP/SKA3 networks were revealed in LUAD for their RBP-involved mechanisms. SKA3 could serve as a potential biomarker for OS prognosis and immunotherapy in LUAD. LncRNA/RBP/SKA3 networks were identified in LUAD for their RBP-involved mechanisms, paving the way for further experimental verifications.

Histology Agnostic Drug Development: An Updated Review

Recent advancements in oncology have led to the development of histology-agnostic therapies, which target genetic alterations irrespective of the tumor's tissue of origin. This review aimed to provide a comprehensive update on the current state of histology-agnostic drug development, focusing on key therapies, including pembrolizumab, larotrectinib, entrectinib, dostarlimab, dabrafenib plus trametinib, selpercatinib, trastuzumab deruxtecan, and reprotrectinib. We performed a detailed analysis of each therapy's mechanism of action, clinical trial outcomes, and associated biomarkers. The review further explores challenges in drug resistance, such as adaptive signaling pathways and neoantigen variability, as well as diagnostic limitations in identifying optimal patient populations. While these therapies have demonstrated efficacy in various malignancies, significant hurdles remain, including intratumoral heterogeneity and resistance mechanisms that diminish treatment effectiveness. We propose considerations for refining trial designs and emerging biomarkers, such as tumor neoantigen burden, to enhance patient selection. These findings illustrate the transformative potential of histology-agnostic therapies in precision oncology but highlight the need for continued research to optimize their use and overcome existing barriers.

Triple-Negative Breast Cancer: Tumor Immunogenicity and Beyond

Triple-negative breast cancer (TNBC) is a breast malignancy with a poor prognosis and limited therapeutic options. Many studies show that TNBC exhibits heterogeneity across clinical, histopathological, and molecular levels. In this review, we discuss the immunogenic features of TNBC with a focus on immunotherapy and the current standard of care in the neoadjuvant, adjuvant, and metastatic setting. In addition, we address the ongoing research on immunotherapy, antibody-drug conjugates (ADCs), poly ADP-ribose polymerase (PARP) inhibitors, and future challenges in the treatment of this entity.

Tumour mutational burden: clinical utility, challenges and emerging improvements

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

Breaking Boundaries: Immunotherapy for Myeloid Malignancies

Immunotherapy has revolutionized the treatment of myeloid oncologic diseases, particularly for patients resistant to chemotherapy or ineligible for allogeneic stem cell transplantation due to age or fitness constraints. As our understanding of the immunopathogenesis of myeloid malignancies expands, so too do the treatment options available to patients. Immunotherapy in myeloid malignancies, however, faces numerous challenges due to the dynamic nature of the disease, immune dysregulation, and the development of immune evasion mechanisms. This review outlines the progress made in the field of immunotherapy for myeloid malignancies, addresses its challenges, and provides insights into future directions in the field.

Plasma versus Tissue Tumor Mutational Burden as Biomarkers of Durvalumab plus Tremelimumab Response in Patients with Metastatic Colorectal Cancer in the CO.26 Trial

PURPOSE

Tissue-derived tumor mutation burden (TMB) of ≥10 mutations/Mb is a histology-agnostic biomarker for the immune checkpoint inhibitor (ICI) pembrolizumab. However, the dataset in which this was validated lacked colorectal cancers (CRC), and there is limited evidence for immunotherapy benefits in CRC using this threshold.

PATIENTS AND METHODS

CO.26 was a randomized phase II study of 180 patients, comparing durvalumab and tremelimumab (D + T, n = 119 patients) versus best supportive care (BSC; n = 61 patients). ctDNA sequencing was available for 168 patients (n = 118 D + T; n = 50), of whom 165 had evaluable plasma TMB (pTMB). Tissue sequencing was available for 108 patients. Optimal thresholds for stratifying patients based on OS were determined using a minimal P value approach. This report includes the final OS analysis.

RESULTS

Tissue TMB ≥10 mutations/Mb was not predictive of benefit from D + T compared with BSC in microsatellite stable (MSS) metastatic CRC [HR, 0.71 (95% CI, 0.28-1.80); P = 0.47]. No tissue TMB threshold could identify a high TMB group that benefited from ICI. By contrast, plasma TMB (pTMB) ≥28 mutations/Mb was predictive of benefit from D + T [HR, 0.34 (95% CI, 0.13-0.85); P = 0.022], as was clonal pTMB ≥10.6 mutations/Mb [HR, 0.10 (95% CI, 0.014-0.79); P = 0.029] and subclonal pTMB ≥25.9/Mb [HR, 0.20 (95% CI, 0.061-0.69); P = 0.010]. Higher pTMB was associated with length of time on cytotoxic agents (P = 0.021) and prior anti-EGFR exposure (P = 2.44 × 10-06).

CONCLUSIONS

pTMB derived from either clonal or subclonal mutations may identify a group likely to benefit from immunotherapy, although validation is required. Tissue TMB provided no predictive utility for immunotherapy in this trial.

SNHG1: Redefining the Landscape of Hepatocellular Carcinoma through Long Noncoding RNAs

Hepatocellular carcinoma (HCC) represents a global health concern, ranking as the sixth most common malignancy worldwide and the third leading cause of cancer-related mortality. Despite advances in research, the diagnosis and prognosis of such malignancy remain challenging. Alpha-fetoprotein, the current serum biomarker used in the management of HCC, has limited sensitivity and specificity, making early detection and effective management more difficult. Thus, new management approaches in diagnosis and prognosis are needed to improve the outcome and survival of HCC patients. SNHG1 is a long noncoding RNA mainly expressed in the cell and cytoplasm of cells and is consistently upregulated in tissues and cell lines of HCC, where it acts as an important regulator of various processes: modulation of p53 activity, sponging of microRNAs with consequent upregulation of their target mRNAs, regulation of fatty acid, iron and glucose metabolism, and interaction with immune cells. The deregulation of these processes results in abnormal cell division, angiogenesis, and apoptosis, thus promoting various aspects of tumorigenesis, including proliferation, invasion, and migration of cells. Clinically, a higher expression of SNHG1 predicts poorer clinical outcomes by significantly correlating with bigger, less differentiated, and more aggressive tumors, more advanced disease stages, and lower overall survival in HCC patients. This article comprehensively summarizes the current understanding of the multifaceted roles of SNHG1 in the pathogenesis of HCC, while also highlighting its clinicopathological correlations, therefore concluding that it has potential as a biomarker in HCC diagnosis and prognosis.

Whole genome sequencing refines stratification and therapy of patients with clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer, but a comprehensive description of its genomic landscape is lacking. We report the whole genome sequencing of 778 ccRCC patients enrolled in the 100,000 Genomes Project, providing for a detailed description of the somatic mutational landscape of ccRCC. We identify candidate driver genes, which as well as emphasising the major role of epigenetic regulation in ccRCC highlight additional biological pathways extending opportunities for therapeutic interventions. Genomic characterisation identified patients with divergent clinical outcome; higher number of structural copy number alterations associated with poorer prognosis, whereas VHL mutations were independently associated with a better prognosis. The observations that higher T-cell infiltration is associated with better overall survival and that genetically predicted immune evasion is not common supports the rationale for immunotherapy. These findings should inform personalised surveillance and treatment strategies for ccRCC patients.

The genomic landscape of the immune system in lung cancer: present insights and continuing investigations

Lung cancer is one of the most prevalent malignancies worldwide, contributing to over a million cancer-related deaths annually. Despite extensive research investigating the genetic factors associated with lung cancer susceptibility and prognosis, few studies have explored genetic predispositions regarding the immune system. This review discusses the most recent genomic findings related to the susceptibility to or protection against lung cancer, patient survival, and therapeutic responses. The results demonstrated the effect of immunogenetic variations in immune system-related genes associated with innate and adaptive immune responses, cytokine, and chemokine secretions, and signaling pathways. These genetic diversities may affect the crosstalk between tumor and immune cells within the tumor microenvironment, influencing cancer progression, invasion, and prognosis. Given the considerable variability in the individual immunegenomics profiles, future studies should prioritize large-scale analyses to identify potential genetic variations associated with lung cancer using highthroughput technologies across different populations. This approach will provide further information for predicting response to targeted therapy and promotes the development of new measures for individualized cancer treatment.

Optimizing perioperative treatment for potentially resectable stage III squamous cell lung carcinoma: promising results of a condensed four-cycle regimen with tislelizumaband chemotherapy

BACKGROUND

The standard care for resectable non-small cell lung cancer (NSCLC) involves perioperative therapy combining chemotherapy and immune checkpoint inhibitors, typically lasting 6 to 12 months. However, the optimal treatment strategies for potentially resectable squamous cell lung carcinoma (SCC) remain unclear. This Phase 2 trial aimed to assess the efficacy and safety of a condensed four-cycle perioperative treatment regimen with tislelizumab combined with chemotherapy in patients with potentially resectable stage III SCC.

METHODS

Patients with potentially resectable stage IIIA-IIIB (N2) SCC received intravenous tislelizumab, albumin-bound paclitaxel, and carboplatin for up to four cycles. The primary endpoints were major pathologic response (MPR) and incidence of treatment-related adverse events. Safety and potential biomarkers for efficacy prediction were also assessed.

RESULTS

Among 35 enrolled patients, 32 underwent surgery with R0 resection achieved in all cases. MPR was achieved in 24 patients and pathological complete response (pCR) in 14 patients. Radiographic objective response was observed in 31 patients. The 12-month and 24-month event-free survival rate was 85.7 and 61.0%, respectively. Four patients experienced grade 3 or 4 adverse events. Tumor tissue based next-generation sequencing revealed the potential associations between several biomarkers and pathological response, including tumor neoantigen burden score, 18-gene expression profile score, CD8 + T cells, M1/M2 macrophages ratio and interferon-gamma expression level. Besides, circulating tumor DNA (ctDNA) dynamics and concentration were also associated with pathological response and the presence of ctDNA at postoperative month 1 was a strong predictor for disease relapse. Furthermore, metagenomic sequencing in bronchoalveolar lavage fluid demonstrated Streptococcus was the most abundant genus in the pCR group.

CONCLUSIONS

A condensed four-cycle perioperative treatment regimen of tislelizumab combined with chemotherapy demonstrated promising efficacy and manageable toxicities in potentially resectable stage III SCC. Specific biomarkers showed potential for predicting treatment efficacy and the mechanism of superior antitumor response of pCR patients was preliminarily and indirectly explored.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT05024266. Registered August 27, 2021.

Cytoreductive Nephrectomy Following Immunotherapy for Metastatic Renal Cell Carcinoma and IVC Tumor Thrombus Arising from a Horseshoe Kidney

INTRODUCTION

Performing surgery for renal cell carcinoma (RCC) in patients with horseshoe kidneys presents unique anatomic challenges. The complexities of clinical decision-making and technical challenges are further compounded by the presence of both IVC tumor thrombus extension and metastatic disease.

CASE PRESENTATION

We encountered the unique case of a 66-year-old woman with a horseshoe kidney who presented with a 14cm mass in her right kidney with level II tumor thrombus extension into the IVC, retroperitoneal lymphadenopathy, and pulmonary nodules that were biopsy-proven to be consistent with metastatic clear cell RCC (cT3aN1M1). She was treated with combination immune checkpoint inhibition (ICI) and targeted therapy upfront. Given her durable response to systemic therapy, we elected to perform a consolidative cytoreductive nephrectomy for residual ypT3aN0 disease, and she has since remained disease-free radiographically. Using step-by-step illustrative photographs obtained intraoperatively, we detail our surgical approach and highlight technical pearls to manage similar cases of advanced RCC arising from horseshoe kidneys.

CONCLUSION

We present a complex case of metastatic RCC with IVC tumor thrombus arising from a horseshoe kidney. We share our clinical and technical approach to overcoming the medical and surgical challenges inherent to her case. The optimal role and timing of cytoreductive nephrectomy relative to ICI administration continue to evolve based on both tumor- and patient-related factors. Indeed, we favor a multidisciplinary approach to optimize patient outcomes.

Targeting Neoantigens in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer and is currently the third leading cause of cancer-related death in the United States after lung and colon cancer. PDAC is estimated to be the second leading cause of cancer-related death by 2030. The diagnosis at a late stage is the underlying cause for higher mortality and poor prognosis after surgery. Treatment resistance to chemotherapy and immunotherapy results in recurrence after surgery and poor prognosis. Neoantigen burden and CD8+ T-cell infiltration are associated with clinical outcomes in PDAC and paucity of neoantigen-reactive tumor-infiltrating lymphocytes may be the underlying cause for treatment resistance for immunotherapy. This suggests a need to identify additional neoantigens and therapies targeting these neoantigens to improve clinical outcomes in PDAC. In this review, we focus on describing the pathophysiology, current treatment strategies, and treatment resistance in PDAC followed by the need to target neoantigens in PDAC.

Enhancing anticancer activity of macrophages through rational drug combinations

Targeting tumor-associated macrophages (TAMs) is an emerging approach being tested in multiple clinical trials. TAMs, depending on their differentiation state, can exhibit pro- or antitumorigenic functions. For example, the M2-like phenotype represents a protumoral state that can stimulate tumor growth, angiogenesis, metastasis, therapy resistance, and immune evasion by expressing immune checkpoint proteins. In this issue of the JCI, Vaccaro and colleagues utilized an innovative drug screen approach to demonstrate that targeting driver oncogenic signaling pathways concurrently with anti-CD47 sensitizes tumor cells, causing them to undergo macrophage-induced phagocytosis. The combination treatment altered expression of molecules on the tumor cells that typically limit phagocytosis. It also reprogrammed macrophages to an M1-like antitumor state. Moreover, the approach was generalizable to tumor cells with different oncogenic pathways, opening the door to precision oncology-based rationale combination therapies that have the potential to improve outcomes for patients with oncogene-driven lung cancers and likely other cancer types.

Biomarkers and computational models for predicting efficacy to tumor ICI immunotherapy

Numerous studies have shown that immune checkpoint inhibitor (ICI) immunotherapy has great potential as a cancer treatment, leading to significant clinical improvements in numerous cases. However, it benefits a minority of patients, underscoring the importance of discovering reliable biomarkers that can be used to screen for potential beneficiaries and ultimately reduce the risk of overtreatment. Our comprehensive review focuses on the latest advancements in predictive biomarkers for ICI therapy, particularly emphasizing those that enhance the efficacy of programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) inhibitors and cytotoxic T-lymphocyte antigen-4 (CTLA-4) inhibitors immunotherapies. We explore biomarkers derived from various sources, including tumor cells, the tumor immune microenvironment (TIME), body fluids, gut microbes, and metabolites. Among them, tumor cells-derived biomarkers include tumor mutational burden (TMB) biomarker, tumor neoantigen burden (TNB) biomarker, microsatellite instability (MSI) biomarker, PD-L1 expression biomarker, mutated gene biomarkers in pathways, and epigenetic biomarkers. TIME-derived biomarkers include immune landscape of TIME biomarkers, inhibitory checkpoints biomarkers, and immune repertoire biomarkers. We also discuss various techniques used to detect and assess these biomarkers, detailing their respective datasets, strengths, weaknesses, and evaluative metrics. Furthermore, we present a comprehensive review of computer models for predicting the response to ICI therapy. The computer models include knowledge-based mechanistic models and data-based machine learning (ML) models. Among the knowledge-based mechanistic models are pharmacokinetic/pharmacodynamic (PK/PD) models, partial differential equation (PDE) models, signal networks-based models, quantitative systems pharmacology (QSP) models, and agent-based models (ABMs). ML models include linear regression models, logistic regression models, support vector machine (SVM)/random forest/extra trees/k-nearest neighbors (KNN) models, artificial neural network (ANN) and deep learning models. Additionally, there are hybrid models of systems biology and ML. We summarized the details of these models, outlining the datasets they utilize, their evaluation methods/metrics, and their respective strengths and limitations. By summarizing the major advances in the research on predictive biomarkers and computer models for the therapeutic effect and clinical utility of tumor ICI, we aim to assist researchers in choosing appropriate biomarkers or computer models for research exploration and help clinicians conduct precision medicine by selecting the best biomarkers.

Clinically relevant stratification of lung squamous carcinoma patients based on ubiquitinated proteasome genes for 3P medical approach

Relevance

The proteasome is a crucial mechanism that regulates protein fate and eliminates misfolded proteins, playing a significant role in cellular processes. In the context of lung cancer, the proteasome's regulatory function is closely associated with the disease's pathophysiology, revealing multiple connections within the cell. Therefore, studying proteasome inhibitors as a means to identify potential pathways in carcinogenesis and metastatic progression is crucial in in-depth insight into its molecular mechanism and discovery of new therapeutic target to improve its therapy, and establishing effective biomarkers for patient stratification, predictive diagnosis, prognostic assessment, and personalized treatment for lung squamous carcinoma in the framework of predictive, preventive, and personalized medicine (PPPM; 3P medicine).

Methods

This study identified differentially expressed proteasome genes (DEPGs) in lung squamous carcinoma (LUSC) and developed a gene signature validated through Kaplan-Meier analysis and ROC curves. The study used WGCNA analysis to identify proteasome co-expression gene modules and their interactions with the immune system. NMF analysis delineated distinct LUSC subtypes based on proteasome gene expression patterns, while ssGSEA analysis quantified immune gene-set abundance and classified immune subtypes within LUSC samples. Furthermore, the study examined correlations between clinicopathological attributes, immune checkpoints, immune scores, immune cell composition, and mutation status across different risk score groups, NMF clusters, and immunity clusters.

Results

This study utilized DEPGs to develop an eleven-proteasome gene-signature prognostic model for LUSC, which divided samples into high-risk and low-risk groups with significant overall survival differences. NMF analysis identified six distinct LUSC clusters associated with overall survival. Additionally, ssGSEA analysis classified LUSC samples into four immune subtypes based on the abundance of immune cell infiltration with clinical relevance. A total of 145 DEGs were identified between high-risk and low-risk score groups, which had significant biological effects. Moreover, PSMD11 was found to promote LUSC progression by depending on the ubiquitin-proteasome system for degradation.

Conclusions

Ubiquitinated proteasome genes were effective in developing a prognostic model for LUSC patients. The study emphasized the critical role of proteasomes in LUSC processes, such as drug sensitivity, immune microenvironment, and mutation status. These data will contribute to the clinically relevant stratification of LUSC patients for personalized 3P medical approach. Further, we also recommend the application of the ubiquitinated proteasome system in multi-level diagnostics including multi-omics, liquid biopsy, prediction and targeted prevention of chronic inflammation and metastatic disease, and mitochondrial health-related biomarkers, for LUSC 3PM practice.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00352-w.

An analysis pipeline for understanding 6-thioguanine effects on a mouse tumour genome

Mouse tumour models are extensively used as a pre-clinical research tool in the field of oncology, playing an important role in anticancer drugs discovery. Accordingly, in cancer genomics research, the demand for next-generation sequencing (NGS) is increasing, and consequently, the need for data analysis pipelines is likewise growing. Most NGS data analysis solutions to date do not support mouse data or require highly specific configuration for their use. Here, we present a genome analysis pipeline for mouse tumour NGS data including the whole-genome sequence (WGS) data analysis flow for somatic variant discovery, and the RNA-seq data flow for differential expression, functional analysis and neoantigen prediction. The pipeline is based on standards and best practices and integrates mouse genome references and annotations. In a recent study, the pipeline was applied to demonstrate the efficacy of low dose 6-thioguanine (6TG) treatment on low-mutation melanoma in a pre-clinical mouse model. Here, we further this study and describe in detail the pipeline and the results obtained in terms of tumour mutational burden (TMB) and number of predicted neoantigens, and correlate these with 6TG effects on tumour volume. Our pipeline was expanded to include a neoantigen analysis, resulting in neopeptide prediction and MHC class I antigen presentation evaluation. We observed that the number of predicted neoepitopes were more accurate indicators of tumour immune control than TMB. In conclusion, this study demonstrates the usability of the proposed pipeline, and suggests it could be an essential robust genome analysis platform for future mouse genomic analysis.

Genomic Features of Homologous Recombination Deficiency in Breast Cancer: Impact on Testing and Immunotherapy

Genomic instability is one of the well-established hallmarks of cancer. The homologous recombination repair (HRR) pathway plays a critical role in correcting the double-stranded breaks (DSB) due to DNA damage in human cells. Traditionally, the BRCA1/2 genes in the HRR pathway have been tested for their association with breast cancer. However, defects in the HRR pathway (HRD, also termed 'BRCAness'), which has up to 50 genes, have been shown to be involved in tumorigenesis and treatment susceptibility to poly-ADP ribose polymerase inhibitors (PARPis), platinum-based chemotherapy, and immune checkpoint inhibitors (ICIs). A reliable consensus on HRD scores is yet to be established. Emerging evidence suggests that only a subset of breast cancer patients benefit from ICI-based immunotherapy. Currently, albeit with limitations, the expression of programmed death-ligand 1 (PDL1) and tumor mutational burden (TMB) are utilized as biomarkers to predict the favorable outcomes of ICI therapy in breast cancer patients. Preclinical studies demonstrate an interplay between the HRR pathway and PDL1 expression. In this review, we outline the current understanding of the role of HRD in genomic instability leading to breast tumorigenesis and delineate outcomes from various clinical trials. Furthermore, we discuss potential strategies for combining HRD-targeted therapy with immunotherapy to achieve the best healthcare outcomes in breast cancer patients.

Durvalumab plus pazopanib combination in patients with advanced soft tissue sarcomas: a phase II trial

We aimed to determine the activity of the anti-VEGF receptor tyrosine-kinase inhibitor, pazopanib, combined with the anti-PD-L1 inhibitor, durvalumab, in metastatic and/or recurrent soft tissue sarcoma (STS). In this single-arm phase 2 trial (NCT03798106), treatment consisted of pazopanib 800 mg orally once a day and durvalumab 1500 mg once every 3 weeks. Primary outcome was overall response rate (ORR) and secondary outcomes included progression-free survival (PFS), overall survival, disease control rate, immune-related response criteria, and safety. The ORR was 30.4% and the trial met the pre-specified endpoint. The median PFS was 7.7 months (95% confidence interval: 5.7-10.4). The common treatment-related adverse events of grades 3-4 included neutropenia (9 [19.1%]), elevated aspartate aminotransferase (7 [14.9%]), alanine aminotransferase (5 [10.6%]), and thrombocytopenia (4 [8.5%]). In a prespecified transcriptomic analysis, the B lineage signature was a significant key determinant of overall response (P = 0.014). In situ analysis also showed that tumours with high CD20+ B cell infiltration and vessel density had a longer PFS (P = 6.5 × 10-4) than those with low B cell infiltration and vessel density, as well as better response (50% vs 12%, P = 0.019). CD20+ B cell infiltration was identified as the only independent predictor of PFS via multivariate analysis. Durvalumab combined with pazopanib demonstrated promising efficacy in an unselected STS cohort, with a manageable toxicity profile.

Refining PD-1/PD-L1 assessment for biomarker-guided immunotherapy: A review

Anti-programmed cell death ligand 1 (anti-PD-L1)  immunotherapy is an increasingly crucial in cancer treatment. To date, the Federal Drug Administration (FDA) has approved four PD-L1 immunohistochemistry (IHC) staining protocols, commercially available in the form of "kits", facilitating testing for PD-L1 expression. These kits comprise four PD-L1 antibodies on two separate IHC platforms, each utilizing distinct, non-interchangeable scoring systems. Several factors, including tumor heterogeneity and the size of the tissue specimens assessed, can lead to PD-L1 status misclassification, potentially hindering the initiation of therapy. Therefore, the development of more accurate predictive biomarkers to distinguish between responders and non-responders prior to anti-PD-1/PD-L1 therapy warrants further research. Achieving this goal necessitates refining sampling criteria, enhancing current methods of PD-L1 detection, and deepening our understanding of the impact of additional biomarkers. In this article, we review potential solutions to improve the predictive accuracy of PD-L1 assessment in order to more precisely anticipate patients' responses to anti-PD-1/PD-L1 therapy, monitor disease progression and predict clinical outcomes.

Whole genome sequencing refines stratification and therapy of patients with clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer, but a comprehensive description of its genomic landscape is lacking. We report the whole genome sequencing of 778 ccRCC patients enrolled in the 100,000 Genomes Project, providing the most detailed somatic mutational landscape to date. We identify new driver genes, which as well as emphasising the major role of epigenetic regulation in ccRCC highlight additional biological pathways extending opportunities for drug repurposing. Genomic characterisation identified patients with divergent clinical outcome; higher number of structural copy number alterations associated with poorer prognosis, whereas VHL mutations were independently associated with a better prognosis. The twin observations that higher T-cell infiltration is associated with better outcome and that genetically predicted immune evasion is not common supports the rationale for immunotherapy. These findings should inform personalised surveillance and treatment strategies for ccRCC patients.

Comprehensive genomic profiling for oncological advancements by precision medicine

Considerable advancements in next generation sequencing (NGS) techniques have sparked the use of comprehensive genomic profiling (CGP) as a guiding tool for precision-centered oncological treatments. The past two decades have seen the completion of the human genome project, and the consequential invention of NGS. High-throughput sequencing technologies support the discovery and commonplace use of individualized cancer treatments, specifically immune-centered checkpoint inhibitor therapies, and oncogene and tumor suppressor gene targeted therapies. Nevertheless, CGP is not commonly used in all clinical settings. This review investigates the clinically relevant applications of CGP. Studies published between the years 2000-2023 have shown substantial evidence of the benefits of integrating CGP into routine care practice, while also making important comparisons to current-standard oncological treatment strategies. Findings of a comprehensive genomic profile includes predictive, prognostic, and diagnostic biomarkers, together with somatic mutation identification which can indicate the efficacy of immunotherapies and molecularly guided therapies. This review highlights the importance of CGP in identifying driver mutations in tumors that subsequently can be effectively targeted with molecular therapeutics and lead to drug discovery, allowing for increased precision in treating tumors selectively based on their specific genetic mutations, thereby improving patient outcomes.

Advances in Immunotherapy for Hepatocellular Carcinoma (HCC)

Hepatocellular carcinoma (HCC) is the second most common cause of cancer-related deaths in the world. More than half of patients with HCC present with advanced stage, and highly active systemic therapies are crucial for improving outcomes. Immune checkpoint inhibitor (ICI)-based therapies have emerged as novel therapy options for advanced HCC. Only one third of patients achieve an objective response with ICI-based therapies due to primary resistance or acquired resistance. The liver tumor microenvironment is naturally immunosuppressive, and specific mutations in cell signaling pathways allow the tumor to evade the immune response. Next, gene sequencing of the tumor tissue or circulating tumor DNA may delineate resistance mechanisms to ICI-based therapy and provide a rationale for novel combination therapies. In this review, we discuss the results of key clinical trials that have led to approval of ICI-based therapy options in advanced HCC and summarize the ongoing clinical trials. We review resistance mechanisms to ICIs and discuss how immunotherapies may be optimized based on the emerging research of tumor biomarkers and genomic alterations.

Clinicopathological characteristics, molecular landscape, and biomarker landscape for predicting the efficacy of PD-1/PD-L1 inhibitors in Chinese population with mismatch repair deficient urothelial carcinoma: a real-world study

Urothelial carcinoma (UC) with deficient mismatch repair (dMMR) is a specific subtype of UC characterized by the loss of mismatch repair (MMR) proteins and its association with Lynch syndrome (LS). However, comprehensive real-world data on the incidence, clinicopathological characteristics, molecular landscape, and biomarker landscape for predicting the efficacy of PD-1/PD-L1 inhibitors in the Chinese patients with dMMR UC remains unknown. We analyzed 374 patients with bladder urothelial carcinoma (BUC) and 232 patients with upper tract urothelial carcinoma (UTUC) using tissue microarrays, immunohistochemistry, and targeted next-generation sequencing. Results showed the incidence of dMMR UC was higher in the upper urinary tract than in the bladder. Genomic analysis identified frequent mutations in KMT2D and KMT2C genes and LS was confirmed in 53.8% of dMMR UC cases. dMMR UC cases displayed microsatellite instability-high (MSI-H) (PCR method) in 91.7% and tumor mutational burden-high (TMB-H) in 40% of cases. The density of intratumoral CD8+ T cells correlated with better overall survival in dMMR UC patients. Positive PD-L1 expression was found in 20% cases, but some patients positively responded to immunotherapy despite negative PD-L1 expression. Our findings provide valuable insights into the characteristics of dMMR UC in the Chinese population and highlights the relevance of genetic testing and immunotherapy biomarkers for treatment decisions.

Characterization of the genomic alterations in poorly differentiated thyroid cancer

Poorly differentiated thyroid carcinoma (PDTC) is a subtype of thyroid cancer that has a high rate of metastasis or recurrence and a relatively poor prognosis. However, there are few studies that have been conducted on PDTC at the whole protein-coding gene scale. Here, we performed genomic profiling of 15 patients with PDTC originated from follicular thyroid carcinoma using whole exome sequencing and also performed gene functional enrichment analysis of differentially expressed genes (DEGs) for three patients. Further, we investigated genetic variants associated with PDTC progression and the characteristics of clinical pathology. We revealed somatic genomic alterations in the RAF1, MAP2K2, and AKT2 genes that were not reported in previous studies. We confirmed frequent occurrences in the RAS gene in patients with PDTC; the genetic alterations were associated with the RAS-RAF-MEK-ERK/JNK, PI3K-AKT-mTOR signaling pathways, and the cell cycle. DEG analysis showed that immune response was lower in cancer tissues than in normal tissues. Through the association analysis of somatic mutations and the characteristics of clinical pathology from patients with PDTC, the somatic mutations of ABCA12, CLIP1, and ATP13A3 were significantly associated with a vascular invasion phenotype. By providing molecular genetic insight on PDTC, this study may contribute to the discovery of novel therapeutic target candidates.

Radiation-associated secondary malignancies: a novel opportunity for applying immunotherapies

Radiation is commonly used as a treatment intended to cure or palliate cancer patients. Despite remarkable advances in the precision of radiotherapy delivery, even the most advanced forms inevitably expose some healthy tissues surrounding the target site to radiation. On rare occasions, this results in the development of radiation-associated secondary malignancies (RASM). RASM are typically high-grade and carry a poorer prognosis than their non-radiated counterparts. RASM are characterized by a high mutation burden, increased T cell infiltration, and a microenvironment that bears unique inflammatory signatures of prior radiation, including increased expression of various cytokines (e.g., TGF-β, TNF-α, IL4, and IL10). Interestingly, these cytokines have been shown to up-regulate the expression of PD-1 and/or PD-L1-an immune checkpoint receptor/ligand pair that is commonly targeted by immune checkpoint blocking immunotherapies. Here, we review the current understanding of the tumor-immune interactions in RASM, highlight the distinct clinical and molecular characteristics of RASM that may render them immunologically "hot," and propose a rationale for the formal testing of immune checkpoint blockade as a treatment approach for patients with RASM.

Understanding and integrating cytoreductive nephrectomy with immune checkpoint inhibitors in the management of metastatic RCC

Cytoreductive nephrectomy became accepted as standard of care for selected patients with metastatic renal cell carcinoma (mRCC) because of improved survival observed in patients treated with cytoreductive nephrectomy in combination with interferon-α in two randomized clinical trials published in 2001. Over the past two decades, novel systemic therapies have shown higher treatment response rates and improved survival outcomes compared with interferon-α. During this rapid evolution of mRCC treatments, systemic therapies have been the primary focus of clinical trials. Results from multiple retrospective studies continue to suggest an overall survival benefit for selected patients treated with nephrectomy in combination with systemic mRCC treatments, with the notable exception of one debated clinical trial. The optimal timing for surgery is unknown, and proper patient selection remains crucial to improving surgical outcomes. As systemic therapies continue to evolve, clinicians have an increasing need to understand how to incorporate cytoreductive nephrectomy into the management of mRCC.

Tumor Cell-Intrinsic c-Myb Upregulation Stimulates Antitumor Immunity in a Murine Colorectal Cancer Model

The transcription factor c-Myb is overexpressed in many different types of solid tumors, including colorectal cancer. However, its exact role in tumorigenesis is unclear. In this study, we show that tumor-intrinsic c-Myb expression in mouse models of colon cancer and melanoma suppresses tumor growth. Although no differences in proliferation, apoptosis, and angiogenesis of tumors were evident in tumors with distinct levels of c-Myb expression, we observed changes in intratumoral immune cell infiltrates. MC38 tumors with upregulated c-Myb expression showed increased numbers of CD103+ dendritic cells and eosinophils, but decreased tumor-associated macrophages (TAM). Concomitantly, an increase in the number of activated cytotoxic CD8+ T cells upon c-Myb upregulation was observed, which correlated with a pro-inflammatory tumor microenvironment and increased numbers of M1 polarized TAMs. Mechanistically, c-Myb upregulation in immunogenic MC38 colon cancer cells resulted in enhanced expression of immunomodulatory genes, including those encoding β2-microglobulin and IFNβ, and decreased expression of the gene encoding the chemokine receptor CCR2. The increased numbers of activated cytotoxic CD8+ T cells contributed to tumor growth attenuation. In poorly immunogenic CT26, LLC, and B16-BL6 tumor cells, c-Myb upregulation did not affect the immunomodulatory gene expression. Despite this, c-Myb upregulation led to reduced B16-BL6 tumor growth but it did not affect tumor growth of CT26 and LLC tumors. Altogether, we postulate that c-Myb functions as a tumor suppressor in a tumor cell-type specific manner and modulates antitumor immunity.

Prognostic Factors in Advanced Non-Small Cell Lung Cancer Patients Treated with Immunotherapy

Taking into account the huge epidemiologic impact of lung cancer (in 2020, lung cancer accounted for 2,206,771 of the cases and for 1,796,144 of the cancer-related deaths, representing the second most common cancer in female patients, the most common cancer in male patients, and the second most common cancer in male and female patients) and the current lack of recommendations in terms of prognostic factors for patients selection and management, this article aims to provide an overview of the current landscape in terms of currently available immunotherapy treatments and the most promising assessed prognostic biomarkers, highlighting the current state-of-the-art and hinting at future challenges.

Activation-induced deaminase expression defines mature B cell lymphoma in the mouse

Germinal centers (GCs) are the sites of secondary antibody diversification and underlie the mechanism of action of many vaccination strategies. Activation-induced deaminase (AID) triggers secondary antibody diversification through the introduction of somatic changes in immunoglobulin genes which lead to the generation of antibodies of higher affinity and more specialized effector functions. However, AID can also target other genomic regions, giving rise to mutations and chromosome translocations with oncogenic potential. Many human lymphomas originate from mature B cells that have undergone the GC reaction, such as the diffuse large B cell lymphoma, the follicular lymphoma and Burkitt lymphoma, and carry chromosome translocations. Mature B cell lymphomagenesis has been modeled in the mouse by the genetic introduction of chromosome translocations. Here, we present an in-depth characterization of one such model, λ-MYC mice. We found that young pre-tumor stage mice had a prominent block in early B cell differentiation that resulted in the generation of very aggressive tumors lacking surface B cell receptor (BCR) expression, indicating that a large fraction of tumors in λ-MYC mice arise from B cell precursors rather than from mature B cells. Further, we assessed the contribution of AID to B cell lymphomagenesis in λ-MYC mice by using a genetic tracer of historical AID expression. Only a fraction of tumors contained cells of GC origin as defined by AID expression. AID-experienced tumors associated with longer survival and resembled mature B cell lymphomas. Thus, AID expression defines Burkitt lymphomagenesis in λ-MYC mice.

Lacking Immunotherapy Biomarkers for Biliary Tract Cancer: A Comprehensive Systematic Literature Review and Meta-Analysis

BACKGROUND

Immunotherapy has recently been incorporated into the spectrum of biliary tract cancer (BTC) treatment. The identification of predictive response biomarkers is essential in order to identify those patients who may benefit most from this novel treatment option. Here, we propose a systematic literature review and a meta-analysis of PD-1, PD-L1, and other immune-related biomarker expression levels in patients with BTC.

METHODS

Prisma guidelines were followed for this systematic review and meta-analysis. Eligible studies were searched on PubMed. Studies published between 2017 and 2022, reporting data on PD-1/PD-L1 expression and other immune-related biomarkers in patients with BTC, were considered eligible.

RESULTS

A total of 61 eligible studies were identified. Despite the great heterogeneity between 39 studies reporting data on PD-L1 expression, we found a mean PD-L1 expression percentage (by choosing the lowest cut-off per study) of 25.6% (95% CI 21.0 to 30.3) in BTCs. The mean expression percentages of PD-L1 were 27.3%, 21.3%, and 27.4% in intrahepatic cholangiocarcinomas (iCCAs-15 studies), perihilar-distal CCAs (p/dCCAs-7 studies), and gallbladder cancer (GBC-5 studies), respectively. Furthermore, 4.6% (95% CI 2.38 to 6.97) and 2.5% (95% CI 1.75 to 3.34) of BTCs could be classified as TMB-H and MSI/MMRd tumors, respectively.

CONCLUSION

From our analysis, PD-L1 expression was found to occur approximately in 26% of BTC patients, with minimal differences based on anatomical location. TMB-H and MSI molecular phenotypes occurred less frequently. We still lack a reliable biomarker, especially in patients with mismatch-proficient tumors, and we must need to make an effort to conceive new prospective biomarker discovery studies.

Tumor neoantigens: Novel strategies for application of cancer immunotherapy

Neoantigen-targeted immunotherapy is a rapidly advancing field that holds great promise for treating cancer. The recognition of antigens by immune cells is a crucial step in tumor-specific killing, and neoantigens generated by mutations in cancer cells possess high immunogenicity and are selectively expressed in tumor cells, making them an attractive therapeutic target. Currently, neoantigens find utility in various domains, primarily in the realm of neoantigen vaccines such as DC vaccines, nucleic acid vaccines, and synthetic long peptide vaccines. Additionally, they hold promise in adoptive cell therapy, encompassing tumor-infiltrating cells, T cell receptors, and chimeric antigen receptors which are expressed by genetically modified T cells. In this review, we summarized recent progress in the clinical use of tumor vaccines and adoptive cell therapy targeting neoantigens, discussed the potential of neoantigen burden as an immune checkpoint in clinical settings. With the aid of state-of-the-art sequencing and bioinformatics technologies, together with significant advancements in artificial intelligence, we anticipated that neoantigens will be fully exploited for personalized tumor immunotherapy, from screening to clinical application.

Social, Genetics and Histopathological Factors Related to Titin (TTN) Gene Mutation and Survival in Women with Ovarian Serous Cystadenocarcinoma: Bioinformatics Analysis

Several factors may increase the risk of development of ovarian cancer. In this study, we investigated the relationship between social, genetic, and histopathologic factors in women with ovarian serous cystadenocarcinoma and titin (TTN) mutations, whether the TTN gene mutation may be a predictor, and its impact on mortality and survival in these patients. A total of 585 samples from patients with ovarian serous cystadenocarcinoma were collected from The Cancer Genome Atlas and PanCancer Atlas through the cBioPortal for analysis of social, genetic, and histopathological factors. Logistic regression was used to investigate whether TTN mutation could be a predictor, and the Kaplan-Meier method was applied to analyze survival time. TTN mutation frequency did not differ between age at diagnosis, tumor stage, and race, and was related to increased Buffa hypoxia score (p = 0.004), mutation count (p < 0.0001), Winter hypoxia Score (p = 0.030), nonsynonymous tumor mutation burden (TMB) (p < 0.0001), and reduced microsatellite instability sensor score (p = 0.010). The number of mutations (p < 0.0001) and winter hypoxia score (p = 0.008) were positively associated with TTN mutations, and nonsynonymous TMB (p < 0.0001) proved to be a predictor. Mutated TTN affects the score of genetic variables involved in cancer cell metabolism in ovarian cystadenocarcinoma.

Role of Surgical Pathologist for Detection of Predictive Immuno-oncological Factors in Breast Cancer

Immune checkpoint inhibitors (ICIs) have changed therapy strategies in breast cancer (BC) patients suffering from triple-negative breast cancer (TNBC). For example, in Europe the anti-programmed cell death 1 ligand 1 (PD-L1) ICI Azetolizumab is approved for adult patients with locally advanced or metastasized TNBC (mTNBC), depending on the immunohistochemical (IHC) PD-L1 expression of immune cells in the tumor area [immune cell (IC) score ≥1%); the anti-programmed cell death 1 (PD-1) ICI pembrolizumab is approved for mTNBC if PD-L1 Combined Positive Score (CPS), that is PD-L1 expression on tumor and/or immune cells, is ≥10. For early TNBC, in contrast, neoadjuvant use of pembrolizumab is approved in the United States and Europe independent from PD-L1 IHC expression. The determination of PD-L1 expression in tumor tissue to predict response to ICI therapy requires sensitive immunostaining with appropriate primary antibodies and staining protocols and a standardized and meticulous assessment of PD-L1 IHC stained breast cancer tissue slides. For the selection of the test material and continuous quality control of the dyeing, high standards must be applied. The evaluation is carried out according to various evaluation algorithms (scores). Here, the role of PD-L1 in BC and the currently most relevant PD-L1 assays and scores for TNBC will be explained. Furthermore, other tissue-based biomarkers potentially predictive for ICI therapy response in BC, for example, tumor mutational burden (TMB), will be presented in this review.

Emerging organoid-immune co-culture models for cancer research: from oncoimmunology to personalized immunotherapies

In the past decade, treatments targeting the immune system have revolutionized the cancer treatment field. Therapies such as immune checkpoint inhibitors have been approved as first-line treatment in a variety of solid tumors such as melanoma and non-small cell lung cancer while other therapies, for instance, chimeric antigen receptor (CAR) lymphocyte transfer therapies, are still in development. Although promising results are obtained in a small subset of patients, overall clinical efficacy of most immunotherapeutics is limited due to intertumoral heterogeneity and therapy resistance. Therefore, prediction of patient-specific responses would be of great value for efficient use of costly immunotherapeutic drugs as well as better outcomes. Because many immunotherapeutics operate by enhancing the interaction and/or recognition of malignant target cells by T cells, in vitro cultures using the combination of these cells derived from the same patient hold great promise to predict drug efficacy in a personalized fashion. The use of two-dimensional cancer cell lines for such cultures is unreliable due to altered phenotypical behavior of cells when compared with the in vivo situation. Three-dimensional tumor-derived organoids, better mimic in vivo tissue and are deemed a more realistic approach to study the complex tumor-immune interactions. In this review, we present an overview of the development of patient-specific tumor organoid-immune co-culture models to study the tumor-specific immune interactions and their possible therapeutic infringement. We also discuss applications of these models which advance personalized therapy efficacy and understanding the tumor microenvironment such as: (1) Screening for efficacy of immune checkpoint inhibition and CAR therapy screening in a personalized manner. (2) Generation of tumor reactive lymphocytes for adoptive cell transfer therapies. (3) Studying tumor-immune interactions to detect cell-specific roles in tumor progression and remission. Overall, these onco-immune co-cultures might hold a promising future toward developing patient-specific therapeutic approaches as well as increase our understanding of tumor-immune interactions.

Current Trends in Neoantigen-Based Cancer Vaccines

Cancer immunotherapies are treatments that use drugs or cells to activate patients’ own immune systems against cancer cells. Among them, cancer vaccines have recently been rapidly developed. Based on tumor-specific antigens referred to as neoantigens, these vaccines can be in various forms such as messenger (m)RNA and synthetic peptides to activate cytotoxic T cells and act with or without dendritic cells. Growing evidence suggests that neoantigen-based cancer vaccines possess a very promising future, yet the processes of immune recognition and activation to relay identification of a neoantigen through the histocompatibility complex (MHC) and T-cell receptor (TCR) remain unclear. Here, we describe features of neoantigens and the biological process of validating neoantigens, along with a discussion of recent progress in the scientific development and clinical applications of neoantigen-based cancer vaccines.