Tumor mutational load predicts survival after immunotherapy across multiple cancer types

Pan-Cancer Analysis of ART1 and its Potential Value in Gastric Cancer

Objective: To comprehensively explore the impact of Mono-ADP-ribosyltransferases-1 expression on both prognosis and the intricate landscape of the tumor immune microenvironment across diverse cancer types, our study seeks to delve into the multifaceted interplay between Mono-ADP-ribosyltransferases-1 expression levels and their implications for clinical outcomes and the dynamic milieu of immune responses within tumors. Methods: Genomic, transcriptomic, and clinical datasets spanning diverse cancer types were meticulously curated from The Cancer Genome Atlas and Genotypic Tissue Expression repositories. Initially, our inquiry focused on discerning the prognostic significance and immunological implications of Mono-ADP-ribosyltransferases-1 expression across this heterogeneous spectrum of malignancies. Subsequently, we scrutinized the relationships between Mono-ADP-ribosyltransferases-1 expression levels and a spectrum of factors including RNA modification genes, genetic mutations, and the emergent concept of tumor stemness. Employing functional enrichment analyses, we endeavored to unravel the underlying mechanistic pathways modulated by Mono-ADP-ribosyltransferases-1. Leveraging Bayesian co-localization analysis, we sought to discern the spatial convergence of Mono-ADP-ribosyltransferases-1 expression particularly within the context of digestive tract tumors. Lastly, to corroborate our findings, we conducted in vitro experiments, specifically focusing on Gastric Cancer, thus corroborating the putative oncogenic role attributed to Mono-ADP-ribosyltransferases-1 in this malignancy. Results: Across diverse tumor types, Mono-ADP-ribosyltransferases-1 expression exhibits distinctive patterns compared to normal and adjacent tissues, thereby intertwining with the prognostic outcomes of numerous cancer patients. Noteworthy findings from our immune role identification underscore the pivotal involvement of Mono-ADP-ribosyltransferases-1 in the landscape of tumor immunotherapy. Furthermore, Kyoto Encyclopedia of Genes and Genomes analysis elucidates the enrichment of Mono-ADP-ribosyltransferases-1-associated genes predominantly within the NF-kB, Foxo, and PI3K-Akt signaling cascades, shedding light on potential mechanistic pathways underlying its influence. Bayesian co-localization analysis unveils a compelling genetic correlation between Mono-ADP-ribosyltransferases-1 and digestive tract tumors, accentuating its relevance within this specific oncological domain. Importantly, experimental validation attests to the therapeutic promise of targeting Mono-ADP-ribosyltransferases-1 in the treatment paradigm of gastric cancer, thereby underscoring its potential as a viable therapeutic target deserving of further exploration and clinical translation. Conclusion: This comprehensive pan-cancer analysis unveils crucial insights into the intricate role played by Mono-ADP-ribosyltransferases-1 in the tumorigenesis of diverse malignancies, thereby establishing a robust theoretical framework for subsequent in-depth investigations. Leveraging these insights, targeting Mono-ADP-ribosyltransferases-1-related signaling pathways within the dynamic tumor microenvironment emerges as a promising avenue for novel therapeutic interventions in the realm of tumor immunotherapy. By delineating the interplay between Mono-ADP-ribosyltransferases-1 expression and tumorigenic processes across various cancer types, this study paves the way for innovative therapeutic strategies aimed at disrupting oncogenic signaling cascades and bolstering immune-mediated antitumor responses.

Integrated Exploration of Epigenetic Dysregulation Reveals a Stemness/EMT Subtype and MMP12 Linked to the Progression and Prognosis in Hepatocellular Carcinoma

Epigenetic dysregulation drives aberrant transcriptional programs playing a critical role in hepatocellular carcinoma (HCC), which may provide novel insights into the heterogeneity of HCC. This study performed an integrated exploration on the epigenetic dysregulation of miRNA and methylation. We discovered and validated three patterns endowed with gene-related transcriptional traits and clinical outcomes. Specially, a stemness/epithelial-mesenchymal transition (EMT) subtype was featured by immune exhaustion and the worst prognosis. Besides, MMP12, a characteristic gene, was highly expressed in the stemness/EMT subtype, which was verified as a pivotal regulator linked to the unfavorable prognosis and further proven to promote tumor proliferation, invasion, and metastasis in vitro experiments. Proteomic analysis by mass spectrometry sequencing also indicated that the overexpression of MMP12 was significantly associated with cell proliferation and adhesion. Taken together, this study unveils innovative insights into epigenetic dysregulation and identifies a stemness/EMT subtype-specific gene, MMP12, correlated with the progression and prognosis of HCC.

Clinicopathologic features, concurrent genomic alterations, and clinical outcomes of patients with KRAS G12D mutations in resected lung adenocarcinoma

BACKGROUND

In light of the ongoing clinical development of KRAS G12D-specific inhibitors, we sought to investigate the clinicopathologic, co-occurring genomic features and outcomes of patients with KRAS G12D-mutant lung adenocarcinoma.

METHODS

3828 patients with completely resected primary lung adenocarcinomas were examined for KRAS mutations between 2008 and 2020. The association between KRAS G12D and clinicopathologic features, molecular profiles, and outcomes was investigated.

RESULTS

65 patients (1.7%) with KRAS G12D-mutant lung adenocarcinoma were identified. KRAS G12D mutation was more frequent in males, former/current smokers, radiologic solid tumors, and invasive mucinous adenocarcinoma. TP53 and STK11 were the two most frequent concomitant mutations in the KRAS G12D group. KRAS G12D mutation did not appear to be a prognostic factor in resected stage I-III lung adenocarcinomas, while KRAS non-G12D mutation was related to worse survival, especially in stage I tumors. KRAS G12D mutations were associated with positive but low (1-49%) PD-L1 expression compared to negative (<1%), while KRAS non-G12D mutation was associated with high PD-L1 expression (≥50%). TP53 co-mutation indicated higher PD-L1 expression, while STK11 co-mutation had a negligible impact on PD-L1 expression. Furthermore, data mining of MSK datasets from cBioPortal revealed that KRAS G12D and SKT11 co-mutation were associated with a diminished response to immunotherapy.

CONCLUSIONS

KRAS G12D-mutant lung adenocarcinoma harbored unique clinicopathologic and genomic characteristics. Despite not being prognostic in resected lung adenocarcinoma, KRAS G12D might be a valuable biomarker in combination with certain co-mutations for identifying relevant subgroups of patients that could eventually influence treatment regimens.

Differential Responses to Immune Checkpoint Inhibitors are Governed by Diverse Mismatch Repair Gene Alterations

PURPOSE

The response to immune checkpoint inhibitors (ICI) in deficient mismatch repair (dMMR) colorectal cancer and endometrial cancer is variable. Here, we explored the differential response to ICIs according to different mismatch repair alterations.

EXPERIMENTAL DESIGN

Colorectal cancer (N = 13,701) and endometrial cancer (N = 3,315) specimens were tested at Caris Life Sciences. Median overall survival (mOS) was estimated using Kaplan-Meier. The prediction of high-, intermediate-, and low-affinity epitopes by tumor mutation burden (TMB) values was conducted using R-squared (R2).

RESULTS

Compared with mutL (MLH1 and PMS2) co-loss, the mOS was longer in mutS (MSH2 and MSH6) co-loss in all colorectal cancer (54.6 vs. 36 months; P = 0.0.025) and endometrial cancer (81.5 vs. 48.2 months; P < 0.001) patients. In ICI-treated patients, the mOS was longer in mutS co-loss in colorectal cancer [not reached (NR) vs. 36 months; P = 0.011). In endometrial cancer, the mOS was NR vs. 42.2 months; P = 0.711]. The neoantigen load (NAL) in mutS co-loss compared with mutL co-loss was higher in colorectal cancer (high-affinity epitopes: 25.5 vs. 19; q = 0.017, intermediate: 39 vs. 32; q = 0.004, low: 87.5 vs. 73; q < 0.001) and endometrial cancer (high-affinity epitopes: 15 vs. 11; q = 0.002, intermediate: 27.5 vs. 19; q < 0.001, low: 59 vs. 41; q < 0.001), respectively. R2 ranged from 0.25 in mutS co-loss colorectal cancer to 0.95 in mutL co-loss endometrial cancer.

CONCLUSIONS

Patients with mutS co-loss experienced longer mOS in colorectal cancer and endometrial cancer and better response to ICIs in colorectal cancer. Among all explored biomarkers, NAL was higher in mutS co-loss and may be a potential driving factor for the observed better outcomes. TMB did not reliably predict NAL.

Immunologic tumor microenvironment modulators for turning cold tumors hot

Tumors can be classified into distinct immunophenotypes based on the presence and arrangement of cytotoxic immune cells within the tumor microenvironment (TME). Hot tumors, characterized by heightened immune activity and responsiveness to immune checkpoint inhibitors (ICIs), stand in stark contrast to cold tumors, which lack immune infiltration and remain resistant to therapy. To overcome immune evasion mechanisms employed by tumor cells, novel immunologic modulators have emerged, particularly ICIs targeting cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and programmed cell death protein 1/programmed death-ligand 1(PD-1/PD-L1). These agents disrupt inhibitory signals and reactivate the immune system, transforming cold tumors into hot ones and promoting effective antitumor responses. However, challenges persist, including primary resistance to immunotherapy, autoimmune side effects, and tumor response heterogeneity. Addressing these challenges requires innovative strategies, deeper mechanistic insights, and a combination of immune interventions to enhance the effectiveness of immunotherapies. In the landscape of cancer medicine, where immune cold tumors represent a formidable hurdle, understanding the TME and harnessing its potential to reprogram the immune response is paramount. This review sheds light on current advancements and future directions in the quest for more effective and safer cancer treatment strategies, offering hope for patients with immune-resistant tumors.

Artificial neural network identified a 20-gene panel in predicting immunotherapy response and survival benefits after anti-PD1/PD-L1 treatment in glioblastoma patients

BACKGROUND

Immune checkpoint inhibitors (ICIs) are a promising immunotherapy approach, but glioblastoma clinical trials have not yielded satisfactory results.

OBJECTIVE

To screen glioblastoma patients who may benefit from immunotherapy.

METHODS

Eighty-one patients receiving anti-PD1/PD-L1 treatment from a large-scale clinical trial and 364 patients without immunotherapy from The Cancer Genome Atlas (TCGA) were included. Patients in the ICI-treated cohort were divided into responders and nonresponders according to overall survival (OS), and the most critical responder-relevant features were screened using random forest (RF). We constructed an artificial neural network (ANN) model and verified its predictive value with immunotherapy response and OS.

RESULTS

We defined two groups of ICI-treated glioblastoma patients with large differences in survival benefits as nonresponders (OS ≤6 months, n = 18) and responders (OS ≥17 months, n = 8). No differentially mutated genes were observed between responders and nonresponders. We performed RF analysis to select the most critical responder-relevant features and developed an ANN with 20 input variables, five hidden neurons and one output neuron. Receiver operating characteristic analysis and the DeLong test demonstrated that the ANN had the best performance in predicting responders, with an AUC of 0.97. Survival analysis indicated that ANN-predicted responders had significantly better OS rates than nonresponders.

CONCLUSION

The 20-gene panel developed by the ANN could be a promising biomarker for predicting immunotherapy response and prognostic benefits in ICI-treated GBM patients and may guide oncologists to accurately select potential responders for the preferential use of ICIs.

HER2 expression and genOmic characterization of rESected brain metastases from colorectal cancer: the HEROES study

BACKGROUND

Little is known about prognostic factors of brain metastases (BM) from colorectal cancer (CRC). HER2 amplification/overexpression (HER2+) was previously described; its impact on prognosis remains uncertain.

METHODS

In the translational study HEROES, extensive molecular analysis was performed on primary CRC (prCRC) and their matched resected BM by means of NGS comprehensive genomic profiling and HER2 status as assessed by immunohistochemical/ in situ hybridization. Count of tumour-infiltrating lymphocytes (TILs) was also performed.

PRIMARY OBJECTIVE

to describe the molecular landscape of paired BM/prCRC.

SECONDARY OBJECTIVES

to search for new prognostic biomarkers of outcome after BM resection: intracranial-only Progression-Free Survival (BM-iPFS), Progression-Free Survival (BM-PFS), and Overall Survival (BM-OS).

RESULTS

Out of 22 patients having paired samples of prCRC and BM, HER2+ was found on 4 (18%) BM, 3 (75%) of which also HER2+ in matched prCRC. Lower tumour mutation burden (HR 3.08; 95%CI 1.06-8.93; p = 0.0386) and HER2-negative BM (HER2neg) (HR 7.75;95%CI 1.97-30.40; p = 0.0033) were associated with longer BM-iPFS; HER2neg BM (HR 3.44; 95%CI 1.03-11.53; p = 0.0449) and KRASmut BM (HR 0.31; 95%CI 0.12-0.80; p = 0.0153) conferred longer BM-PFS. Longer BM-OS was found in pts with TILs-enriched (≥1.6/HPF) BM (HR 0.11; 95%CI0.01-0.91; p = 0.0403).

CONCLUSIONS

This study shows HER2+ enrichment in both BM and their prCRC. TILs-enriched BM conferred better BM-OS.

Tumor mutational burden in colorectal cancer: Implications for treatment

Although immune checkpoint inhibitors have revolutionized the treatment of several advanced solid cancers, in colorectal cancer, the transformative benefit of these innovative medicines is currently limited to those with deficient mismatch repair or high microsatellite instability. Tumor mutational burden (TMB) has emerged as a potential predictor of immunotherapy benefit, but the lack of standardization in its assessment and reporting has hindered the introduction of this biomarker in routine clinical practice. Here, we compiled 45 colorectal cancer studies utilizing numerical thresholds for high-TMB. In this group of studies, TMB cut-offs ranged from 6.88 to 41 mut/Mb and were most often set at 10, 17, or 20 mut/Mb. Additionally, we observed divergent TMB definitions and inconsistent disclosure of specific methodological details, which collectively emphasize the substantial lack of harmonization within the field. Ongoing efforts to harmonize TMB assessment will be critical to validate TMB as a predictive marker of immunotherapy response.

Deciphering disulfidptosis: Uncovering a lncRNA-based signature for prognostic assessment, personalized immunotherapy, and therapeutic agent selection in lung adenocarcinoma patients

BACKGROUND

Disulfidptosis, a recently identified type of regulated cell death, plays critical roles in various biological processes of cancer; however, whether they can impact the prognosis of lung adenocarcinoma (LUAD) remains to be fully elucidated. We aimed to adopt this concept to develop and validate a lncRNA signature for LUAD prognostic prediction.

METHODS

For this study, the TCGA-LUAD dataset was used as the training cohort, and multiple datasets from the GEO database were pooled as the validation cohort. Disulfidptosis regulated genes were obtained from published studies, and various statistical methods, including Kaplan-Meier (KM), Cox, and LASSO, were used to train our gene signature DISULncSig. We utilized KM analysis, COX analysis, receiver operating characteristic analysis, time-dependent AUC analysis, principal component analysis, nomogram predictor analysis, and functional assays in our validation process. We also compared DISULncSig with previous studies. We performed analyses to evaluate DISULncSig's immunotherapeutic ability, focusing on eight immune algorithms, TMB, and TIDE. Additionally, we investigated potential drugs that could be effective in treating patients with high-risk scores. Additionally qRT-PCR examined the expression patterns of DISULncSig lncRNAs, and the ability of DISULncSig in pan-cancer was also assessed.

RESULTS

DISULncSig containing twelve lncRNAs was trained and showed strong predictive ability in the validation cohort. Compared with previous similar studies, DISULncSig had more prognostic ability advantages. DISULncSig was closely related to the immune status of LUAD, and its tight relationship with checkpoints KIR2DL3, IL10, IL2, CD40LG, SELP, BTLA, and CD28 may be the key to its potential immunotherapeutic ability. For the high DISULncSig score population, we found ten drug candidates, among which epothilone-b may have the most potential. The pan-cancer analysis found that DISULncSig was a risk factor in multiple cancers. Additionally, we discovered that some of the DISULncSig lncRNAs could play crucial roles in specific cancer types.

CONCLUSION

The current study established a powerful prognostic DISULncSig signature for LUAD that was also valid for most pan-cancers. This signature could serve as a potential target for immunotherapy and might help the more efficient application of drugs to specific populations.

Outcome of First-Line Treatment With Pembrolizumab According to KRAS/TP53 Mutational Status for Nonsquamous Programmed Death-Ligand 1-High (≥50%) NSCLC in the German National Network Genomic Medicine Lung Cancer

INTRODUCTION

Programmed death-ligand 1 expression currently represents the only validated predictive biomarker for immune checkpoint inhibition in metastatic NSCLC in the clinical routine, but it has limited value in distinguishing responses. Assessment of KRAS and TP53 mutations (mut) as surrogate for an immunosupportive tumor microenvironment (TME) might help to close this gap.

METHODS

A total of 696 consecutive patients with programmed death-ligand 1-high (≥50%), nonsquamous NSCLC, having received molecular testing within the German National Network Genomic Medicine Lung Cancer between 2017 and 2020, with Eastern Cooperative Oncology Group performance status less than or equal to 1 and pembrolizumab as first-line palliative treatment, were included into this retrospective cohort analysis. Treatment efficacy and outcome according to KRAS/TP53 status were correlated with TME composition and gene expression analysis of The Cancer Genome Atlas lung adenocarcinoma cohort.

RESULTS

Proportion of KRASmut and TP53mut was 53% (G12C 25%, non-G12C 28%) and 51%, respectively. In KRASmut patients, TP53 comutations increased response rates (G12C: 69.7% versus 46.5% [TP53mut versus wild-type (wt)], p = 0.004; non-G12C: 55.4% versus 39.5%, p = 0.03), progression-free survival (G12C: hazard ratio [HR] = 0.59, p = 0.009, non-G12C: HR = 0.7, p = 0.047), and overall survival (G12C: HR = 0.72, p = 0.16, non-G12C: HR = 0.56, p = 0.002), whereas no differences were observed in KRASwt patients. After a median follow-up of 41 months, G12C/TP53mut patients experienced the longest progression-free survival and overall survival (33.7 and 65.3 mo), which correlated with high tumor-infiltrating lymphocyte densities in the TME and up-regulation of interferon gamma target genes. Proinflammatory pathways according to TP53 status (mut versus wt) were less enhanced and not different in non-G12C and KRASwt, respectively.

CONCLUSIONS

G12C/TP53 comutations identify a subset of patients with a very favorable long-term survival with immune checkpoint inhibitor monotherapy, mediated by highly active interferon gamma signaling in a proinflammatory TME.

Strategies to Improve Drug Delivery Across the Blood-Brain Barrier for Glioblastoma

PURPOSE OF REVIEW

Glioblastoma remains resistant to most conventional treatments. Despite scientific advances in the past three decades, there has been a dearth of effective new treatments. New approaches to drug delivery and clinical trial design are needed.

RECENT FINDINGS

We discuss how the blood-brain barrier and tumor microenvironment pose challenges for development of effective therapies for glioblastoma. Next, we discuss treatments in development that aim to overcome these barriers, including novel drug designs such as nanoparticles and antibody-drug conjugates, novel methods of drug delivery, including convection-enhanced and intra-arterial delivery, and novel methods to enhance drug penetration, such as blood-brain barrier disruption by focused ultrasound and laser interstitial thermal therapy. Lastly, we address future opportunities, positing combination therapy as the best strategy for effective treatment, neoadjuvant and window-of-opportunity approaches to simultaneously enhance therapeutic effectiveness with interrogation of on-treatment biologic endpoints, and adaptive platform and basket trials as imperative for future trial design. New approaches to GBM treatment should account for the blood-brain barrier and immunosuppression by improving drug delivery, combining treatments, and integrating novel clinical trial designs.

Precision Medicine in the Era of Genetic Testing: Microsatellite Instability Evolved

The recognized importance of microsatellite instability (MSI) in cancer has evolved considerably in the past 30 years. From its beginnings as a molecular predictor for Lynch syndrome, MSI first transitioned to a universal screening test in all colorectal and endometrial cancers, substantially increasing the identification of patients with Lynch syndrome among cancer patients. More recently, MSI has been shown to be a powerful biomarker of response to immune checkpoint blockade therapy across a diversity of tumor types, and in 2017 was granted Food and Drug Administration approval as the first tumor histology-agnostic biomarker for a cancer therapy. Focusing on colorectal cancer specifically, immune checkpoint blockade therapy has been shown to be highly effective in the treatment of both MSI-high (MSI-H) colon and rectal cancer, with data increasingly suggesting an early role for immune checkpoint blockade therapy in MSI-H colorectal tumors in the neoadjuvant setting, with the potential to avoid more toxic and morbid approaches using traditional chemotherapy, radiation therapy, and surgery. The success of MSI as an immune checkpoint blockade target has inspired ongoing vigorous research to identify new similar targets for immune checkpoint blockade therapy that may help to one day expand the reach of this revolutionary cancer therapy to a wider swath of patients and indications.

A large-scale, multicenter characterization of BRAF G469V/A-mutant non-small cell lung cancer

BACKGROUND

Mutated BRAF is identified in 1%-5% non-small cell lung cancer (NSCLC) patients, with non-V600 mutations accounting for 50%-70% of these. The most common non-V600 mutation is BRAF G469V/A. Currently, there are no targeted therapies available for non-V600 mutated patients. A recent report provided interesting preclinical evidence revealing sensitivity of BRAF G469V to epidermal growth factor receptor (EGFR) inhibitors, raising the possibility of repurposing anti-EGFR agents. It is therefore worthy to characterize the clinical and molecular features of BRAF G469V/A-mutant NSCLC to provide more insights for precision therapy.

METHODS

We conducted a retrospective screening of 25,694 Chinese patients with advanced or metastatic NSCLC to identify individuals with mutated BRAF. Additionally, we performed similar screenings on patients with adenocarcinoma (LUAD) from The Cancer Genome Atlas (TCGA) cohort (n = 567) and the MSKCC cohort (n = 1152). Subsequently, we characterized the clinical and molecular features of the patients carrying BRAF mutations.

RESULTS

BRAF G469V was identified in 28 (0.1%) patients from the Chinese NSCLC cohort and 5 (0.9%) from TCGA-LUAD. Notably, none was identified in the MSKCC cohort. G469A was found in 79 (0.3%) Chinese patients, 2 (0.4%) from TCGA-LUAD, and 9 (0.8%) from the MSKCC cohort. Relative allele frequency analysis suggested most BRAF mutations as driven clones. Tumor mutation burden (median 4 mutations/Mb) was not significantly different between patients carrying G469V, G469A, V600E, or other BRAF mutations. Surprisingly, KRAS mutations were found in approximately 50% of patients with G469V mutation and about 8% of patients with G469A mutation, representing a prominent potential resistance mechanism against EGFR inhibitors. Structural modeling suggested BRAF G469V and G469A as binding partners of gefitinib.

CONCLUSION

Our large-scale analysis characterized the prevalence and mutational landscape of BRAF G469V/A-mutant NSCLC and proposed gefitinib as a potential option, providing a basis for further investigations on treating BRAF-mutated NSCLC.

Prognostic models for immunotherapy in non-small cell lung cancer: A comprehensive review

The introduction of immune checkpoint inhibitors (ICIs) has revolutionized the treatment of lung cancer. Given the limited clinical benefits of immunotherapy in patients with non-small cell lung cancer (NSCLC), various predictors have been shown to significantly influence prognosis. However, no single predictor is adequate to forecast patients' survival benefit. Therefore, it's imperative to develop a prognostic model that integrates multiple predictors. This model would be instrumental in identifying patients who might benefit from ICIs. Retrospective analysis and small case series have demonstrated the potential role of these models in prognostic prediction, though further prospective investigation is required to evaluate more rigorously their application in these contexts. This article presents and summarizes the latest research advancements on immunotherapy prognostic models for NSCLC from multiple omics perspectives and discuss emerging strategies being developed to enhance the domain.

CHEK2 deficiency increase the response to PD-1 inhibitors by affecting the tumor immune microenvironment

Immune checkpoint blockade (ICB) therapy has improved treatment effects in multiple cancers. Gene mutations in the DNA damage repair pathway (DDR) may cause genomic instability and may relate to the efficacy of ICB. Checkpoint kinase 2 (CHEK2) and polymerase epsilon (POLE) are important genes in the DDR. In this study, we aimed to study the impact of CHEK2 deficiency mutations on the response to ICB. We found that tumors with CHEK2 mutations had a significantly higher tumor mutational burden (TMB) compared to those with CHEK2-WT in a pancancer database. We noted that CHEK2 deficiency mutations potentiated the anti-tumor effect of anti-PD-1 therapy in MC38 and B16 tumor-bearing mice with the decrease of tumor volume and tumor weight after anti-PD-1 treatment. Mechanistically, CHEK2 deficiency tumors were with the increased cytotoxic CD8+ T-cell infiltration, especially cytotoxic CD8+ T cells, and modulated the tumor-immune microenvironment with an upregulated immune inflammatory pathway and antigen presentation pathway after anti-PD-1 treatment. Furthermore, murine models with POLE mutations confirmed that CHEK2 deficiency shaped similar mutational and immune landscapes as POLE mutations after anti-PD-1 treatment. Taken together, our results demonstrated that CHEK2 deficiency mutations may increase the response to ICB (eg. anti-PD-1) by influencing the tumor immune microenvironment. This indicated that CHEK2 deficiency mutations were a potentially predictive biomarker and CHEK2 deficiency may potentiate response to immunotherapy.

Identification of prognostic m6A modification patterns and score system in melanoma patients

N6-methyladenosine (m6A) is the most common modification on RNAs and LncRNAs. It plays an important role in cancer stem cell differentiation, T cell differentiation, and immune homeostasis. In this study, we explored the potential roles of m6A modification of RNA in melanoma and investigated the immune cell infiltration in tumor microenvironment in diverse m6Aclusters and different m6Ascore groups. A consensus clustering algorithm determined m6A modification patterns based on 14 m6A regulators, and further explored the biological functions and the connection with TME. An m6A-related gene signature (m6Ascore) was constructed based on m6A-related genes using principal component analysis. Three m6A modification patterns were identified based on 14 m6A regulators, named as m6Aclusters A-C. The prognosis of m6Acluster A was more favorable than m6Aclusters B and C, and it was more closely associated with immune regulation. To quantify the m6A modification patterns of individual tumor, an m6Ascore was constructed, and patients were classified into high and low m6Ascore groups. The low m6Ascore group, which had a favorable prognosis, was more relevant to immunology. The expression of PD-L1 was higher and the immunophenoscore (IPS) revealed stronger response to immunotherapy in the low m6Ascore group. This study identified 3 m6A modification patterns with different immune characteristics and constructed an m6Ascore system to predict prognosis and immunogenicity of patients, which is conducive to clinical prognosis judgment and individual treatment.

Predictive and Prognostic Relevance of Tumor-Infiltrating Immune Cells: Tailoring Personalized Treatments against Different Cancer Types

TIICs are critical components of the TME and are used to estimate prognostic and treatment responses in many malignancies. TIICs in the tumor microenvironment are assessed and quantified by categorizing immune cells into three subtypes: CD66b+ tumor-associated neutrophils (TANs), FoxP3+ regulatory T cells (Tregs), and CD163+ tumor-associated macrophages (TAMs). In addition, many cancers have tumor-infiltrating M1 and M2 macrophages, neutrophils (Neu), CD4+ T cells (T-helper), CD8+ T cells (T-cytotoxic), eosinophils, and mast cells. A variety of clinical treatments have linked tumor immune cell infiltration (ICI) to immunotherapy receptivity and prognosis. To improve the therapeutic effectiveness of immune-modulating drugs in a wider cancer patient population, immune cells and their interactions in the TME must be better understood. This study examines the clinicopathological effects of TIICs in overcoming tumor-mediated immunosuppression to boost antitumor immune responses and improve cancer prognosis. We successfully analyzed the predictive and prognostic usefulness of TIICs alongside TMB and ICI scores to identify cancer's varied immune landscapes. Traditionally, immune cell infiltration was quantified using flow cytometry, immunohistochemistry, gene set enrichment analysis (GSEA), CIBERSORT, ESTIMATE, and other platforms that use integrated immune gene sets from previously published studies. We have also thoroughly examined traditional limitations and newly created unsupervised clustering and deconvolution techniques (SpatialVizScore and ProTICS). These methods predict patient outcomes and treatment responses better. These models may also identify individuals who may benefit more from adjuvant or neoadjuvant treatment. Overall, we think that the significant contribution of TIICs in cancer will greatly benefit postoperative follow-up, therapy, interventions, and informed choices on customized cancer medicines.

Anti-PD-1 antibody in combination with radiotherapy as first-line therapy for unresectable intrahepatic cholangiocarcinoma

BACKGROUND

Unresectable intrahepatic cholangiocarcinoma (iCCA) has a poor prognosis despite treatment with standard combination chemotherapy. We aimed to evaluate the efficacy and safety of radiotherapy in combination with an anti-PD-1 antibody in unresectable iCCA without distant metastases.

METHODS

In this phase II study, patients with histopathologically confirmed unresectable primary or postoperative recurrent iCCA without distant metastases were enrolled. Patients received external radiotherapy with a dose of ≥45 Gy (2-2.5 Gy per fraction), followed by anti-PD-1 immunotherapy (camrelizumab 200 mg once, every 3 weeks) initiated within 7 days after completion of radiotherapy as first-line therapy. The primary endpoint was 1-year progression-free survival (PFS) rate. The secondary end points included safety, objective response rate (ORR), disease control rate (DCR), and overall survival (OS).

RESULTS

From December 2019 to March 2021, 36 patients completed radiotherapy and at least one cycle of immunotherapy and were included in efficacy and safety analyses. The median follow-up was 19.0 months (IQR 12.0-24.0), and the one-year PFS rate was 44.4% (95% CI, 30.8-64.0). The median PFS was 12.0 months (95% CI, 7.5-not estimable); the median OS was 22.0 months (95% CI, 15.0-not estimable). The ORR was 61.1% and the DCR was 86.1%. Seventeen of 36 (47.2%) patients experienced treatment-related adverse effects (AEs) of any grade. The most common AE was reactive cutaneous capillary endothelial proliferation (25.0%). Five (13.9%) patients experienced grade ≥3 treatment-related AEs, including decreased lymphocyte (5.6%), bullous dermatitis (2.8%), decreased platelet count (2.8%), and deep-vein thrombosis (2.8%).

CONCLUSIONS

External radiotherapy plus camrelizumab, as first-line therapy, met its primary endpoint and showed antitumor activity and low toxicity levels in patients with unresectable iCCA without distant metastases, warranting further investigation.

TRIAL REGISTRATION

NCT03898895. Registered 2 April 2019.

The Genomic, Transcriptomic, and Immunologic Landscape of HRAS Mutations in Solid Tumors

Tipifarnib is the only targeted therapy breakthrough for HRAS-mutant (HRASmt) recurrent or metastatic head and neck squamous cell carcinoma (HNSCC). The molecular profiles of HRASmt cancers are difficult to explore given the low frequency of HRASmt. This study aims to understand the molecular co-alterations, immune profiles, and clinical outcomes of 524 HRASmt solid tumors including urothelial carcinoma (UC), breast cancer (BC), non-small-cell lung cancer (NSCLC), melanoma, and HNSCC. HRASmt was most common in UC (3.0%), followed by HNSCC (2.82%), melanoma (1.05%), BC (0.45%), and NSCLC (0.44%). HRASmt was absent in Her2+ BC regardless of hormone receptor status. HRASmt was more frequently associated with squamous compared to non-squamous NSCLC (60% vs. 40% in HRASwt, p = 0.002). The tumor microenvironment (TME) of HRASmt demonstrated increased M1 macrophages in triple-negative BC (TNBC), HNSCC, squamous NSCLC, and UC; increased M2 macrophages in TNBC; and increased CD8+ T-cells in HNSCC (all p < 0.05). Finally, HRASmt was associated with shorter overall survival in HNSCC (HR: 1.564, CI: 1.16-2.11, p = 0.003) but not in the other cancer types examined. In conclusion, this study provides new insights into the unique molecular profiles of HRASmt tumors that may help to identify new targets and guide future clinical trial design.

Uveal melanoma immunogenomics predict immunotherapy resistance and susceptibility

Immune checkpoint inhibition has shown success in treating metastatic cutaneous melanoma but has limited efficacy against metastatic uveal melanoma, a rare variant arising from the immune privileged eye. To better understand this resistance, we comprehensively profile 100 human uveal melanoma metastases using clinicogenomics, transcriptomics, and tumor infiltrating lymphocyte potency assessment. We find that over half of these metastases harbor tumor infiltrating lymphocytes with potent autologous tumor specificity, despite low mutational burden and resistance to prior immunotherapies. However, we observe strikingly low intratumoral T cell receptor clonality within the tumor microenvironment even after prior immunotherapies. To harness these quiescent tumor infiltrating lymphocytes, we develop a transcriptomic biomarker to enable in vivo identification and ex vivo liberation to counter their growth suppression. Finally, we demonstrate that adoptive transfer of these transcriptomically selected tumor infiltrating lymphocytes can promote tumor immunity in patients with metastatic uveal melanoma when other immunotherapies are incapable.

EEPD1 is identified as a predictor of prognosis and immune microenvironment through pan-cancer analysis and related to progression of colorectal cancer

Background

EEPD1 is vital in homologous recombination, while its role in cancer remains unclear.

Methods

We performed multiple pan-cancer analyses of EEPD1 with bioinformatics methods, such as gene expression, gene alterations, Prognosis and enrichment analysis, tumor microenvironment, immune cell infiltration, TMB, MSI, immunotherapy, co-expression of genes, and drug resistance. Finally, RT-qPCR, EdU, and transwell assays helped investigate the impact of EEPD1 on CRC cells.

Results

EEPD1 was dysregulated and correlated with bad prognosis in several cancers. GSVA and GSEA revealed that EEPD1 was primarily associated with the "WNT_BETA_CATENIN_SIGNALING," "ribonucleoprotein complex biogenesis," "Ribosome," and "rRNA processing." The infiltration of CD8+ T cells, MAIT cells, iTreg cells, NK cells, Tc cells, Tex cells, Tfh cells, and Th1 cells were negatively correlated with EEPD1 expression. Additionally, EEPD1 is significantly associated with TMB and MSI in COAD, while enhanced CRC cell proliferation and migration.

Conclusions

EEPD1 was dysregulated in human cancers and correlated with various cancer patient prognoses. The dysregulated EEPD1 expression can affect tumor-infiltrating immune cells and immunotherapy response. Therefore, EEPD1 could act as an oncogene associated with immune cell infiltration in CRC.

Identification of nomogram associated with durable clinical benefit gene for advanced non-small cell lung cancer with sensitivity to responsive to immunotherapy

Background

Immunotherapy has become the standard treatment for advanced non-small cell lung cancer (NSCLC). However, a subset of the most advanced NSCLC patients fails to respond adequately to Immune checkpoint inhibitors (ICIs). Developing new nomograms and integrating prognostic factors are crucial for improving the clinical predictability of NSCLC patients undergoing ICIs.

Methods

Clinical information and genomic data of NSCLC patients undergoing ICIs were retrieved from cBioPortal. Gene alterations associated with durable clinical benefit (DCB) were compared to those linked to no durable benefit (NDB). The Kaplan-Meier plot method was employed for survival analysis, and a novel nomogram was formulated by selecting pertinent clinical variables.

Results

For the NSCLC patients receiving immunotherapy, three subgroups were identified based on the treatment regimen, including anti-PD-1 monotherapy, anti-PD-1 combination with anti-CTLA-4, and first-line treatment. The mutation status of TP53, PGR, PTPRT, RELN, MUC19, LRP1B, and FAT3 was found to be associated with progression-free survival (PFS). Using the clinicopathological parameters and genomic data of the patients, we developed three novel nomograms to predict the prognosis of ICI treatment in different subgroups.

Conclusion

Our study revealed that PGR, PTPRD, RELN, MUC19, LRP1B, and FAT3 mutation could serve as predictive biomarkers. Our systematic nomograms demonstrate significant potential in predicting the prognosis for NSCLC patients with sensitivity to different ICI treatment strategies.

Gene features of tumor-specific T cells relevant to immunotherapy, targeted therapy and chemotherapy in lung cancer

1 Background

In lung cancer, the use of small-molecule inhibitors, chemotherapy and immunotherapy has led to unprecedented survival benefits in selected patients. Considering most patients will experience a relapse within a short period of time due to single drug resistance, combination therapy is also particularly important to improve patient prognosis. Therefore, more robust biomarkers to predict responses to immunotherapy, targeted therapy, chemotherapy and rationally drug combination therapies may be helpful in clinical treatment choices.

2 Methods

We defined tumor-specific T cells (TSTs) and their features (TSTGs) by single-cell RNA sequencing. We applied LASSO regression to filter out the most survival-relevant TSTGs to form the Tumor-specific T cell score (TSTS). Immunological characteristics, enriched pathways, and mutation were evaluated in high- and low TSTS groups.

3 Results

We identified six clusters of T cells as TSTs in lung cancer, and four most robust genes from 9 feature genes expressed only on tumor-specific T cells were screened to construct a tumor-specific T cells score (TSTS). TSTS was positively correlated with immune infiltration and angiogenesis and negatively correlated with malignant cell proliferation. Moreover, potential vascular-immune crosstalk in lung cancer provides the theoretical basis for combined anti-angiogenic and immunotherapy. Noticeable, patients in high TSTS had better response to ICB and targeted therapy and patients in the low TSTS group often benefit from chemotherapy.

4 Conclusion

The proposed TSTS is a promising indicator to predict immunotherapy, targeted therapy and chemotherapy responses in lung cancer patients for helping clinical treatment choices.

A novel tumor mutation-related long non-coding RNA signature for predicting overall survival and immunotherapy response in lung adenocarcinoma

Background

Immunotherapy has changed the treatment landscape for lung cancer. This study aims to construct a tumor mutation-related model that combines long non-coding RNA (lncRNA) expression levels and tumor mutation levels in tumor genomes to detect the possibilities of the lncRNA signature as an indicator for predicting the prognosis and response to immunotherapy in lung adenocarcinoma (LUAD).

Methods

We downloaded the tumor mutation profiles and RNA-seq expression database of LUAD from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were extracted based on the cumulative number of mutations. Cox regression analyses were used to identify the prognostic lncRNA signature, and the prognostic value of the five selected lncRNAs was validated by using survival analysis and the receiver operating characteristic (ROC) curve. We used qPCR to validate the expression of five selected lncRNAs between human lung epithelial and human lung adenocarcinoma cell lines. The ImmuCellAI, immunophenoscore (IPS) scores and Tumor Immune Dysfunction and Exclusion (TIDE) analyses were used to predict the response to immunotherapy for this mutation related lncRNA signature.

Results

A total of 162 lncRNAs were detected among the differentially expressed lncRNAs between the Tumor mutational burden (TMB)-high group and the TMB-low group. Then, five lncRNAs (PLAC4, LINC01116, LINC02163, MIR223HG, FAM83A-AS1) were identified as tumor mutation-related candidates for constructing the prognostic prediction model. Kaplan‒Meier curves showed that the overall survival of the low-risk group was significantly better than that of the high-risk group, and the results of the GSE50081 set were consistent. The expression levels of PD1, PD-L1 and CTLA4 in the low-risk group were higher than those in the high-risk group. The IPS scores and TIDE scores of patients in the low-risk group were significantly higher than those in the high-risk group.

Conclusion

Our findings demonstrated that the five lncRNAs (PLAC4, LINC01116, LINC02163, MIR223HG, FAM83A-AS1) were identified as candidates for constructing the tumor mutation-related model which may serve as an indicator of tumor mutation levels and have important implications for predicting the response to immunotherapy in LUAD.

RUNX1-BMP2 promotes vasculogenic mimicry in laryngeal squamous cell carcinoma via activation of the PI3K-AKT signaling pathway

BACKGROUND

Laryngeal squamous cell carcinoma (LSCC) is one of the most common malignant tumors of the head and neck. Vasculogenic mimicry (VM) is crucial for tumor growth and metastasis and refers to the formation of fluid channels by invasive tumor cells rather than endothelial cells. However, the regulatory mechanisms underlying VM during the malignant progression of LSCC remain largely unknown.

METHODS

Gene expression and clinical data for LSCC were obtained from the TCGA and Gene GEO (GSE27020) databases. A risk prediction model associated with VM was established using LASSO and Cox regression analyses. Based on their risk scores, patients with LSCC were categorized into high- and low-risk groups. The disparities in immune infiltration, tumor mutational burden (TMB), and functional enrichment between these two groups were examined. The core genes in LSCC were identified using the machine learning (SVM-RFE) and WGCNA algorithms. Subsequently, the involvement of bone morphogenetic protein 2 (BMP2) in VM and metastasis was investigated both in vitro and in vivo. To elucidate the downstream signaling pathways regulated by BMP2, western blotting was performed. Additionally, ChIP experiments were employed to identify the key transcription factors responsible for modulating the expression of BMP2.

RESULTS

We established a new precise prognostic model for LSCC related to VM based on three genes: BMP2, EPO, and AGPS. The ROC curves from both TCGA and GSE27020 validation cohorts demonstrated precision survival prediction capabilities, with the nomogram showing some net clinical benefit. Multiple algorithm analyses indicated BMP2 as a potential core gene. Further experiments suggested that BMP2 promotes VM and metastasis in LSCC. The malignant progression of LSCC is promoted by BMP2 via the activation of the PI3K-AKT signaling pathway, with the high expression of BMP2 in LSCC resulting from its transcriptional activation by runt-related transcription factor 1 (RUNX1).

CONCLUSION

BMP2 predicts poor prognosis in LSCC, promotes LSCC VM and metastasis through the PI3K-AKT signaling pathway, and is transcriptionally regulated by RUNX1. BMP2 may be a novel, precise, diagnostic, and therapeutic biomarker of LSCC.

Biomarker discovery with quantum neural networks: a case-study in CTLA4-activation pathways

BACKGROUND

Biomarker discovery is a challenging task due to the massive search space. Quantum computing and quantum Artificial Intelligence (quantum AI) can be used to address the computational problem of biomarker discovery from genetic data.

METHOD

We propose a Quantum Neural Networks architecture to discover genetic biomarkers for input activation pathways. The Maximum Relevance-Minimum Redundancy criteria score biomarker candidate sets. Our proposed model is economical since the neural solution can be delivered on constrained hardware.

RESULTS

We demonstrate the proof of concept on four activation pathways associated with CTLA4, including (1) CTLA4-activation stand-alone, (2) CTLA4-CD8A-CD8B co-activation, (3) CTLA4-CD2 co-activation, and (4) CTLA4-CD2-CD48-CD53-CD58-CD84 co-activation.

CONCLUSION

The model indicates new genetic biomarkers associated with the mutational activation of CLTA4-associated pathways, including 20 genes: CLIC4, CPE, ETS2, FAM107A, GPR116, HYOU1, LCN2, MACF1, MT1G, NAPA, NDUFS5, PAK1, PFN1, PGAP3, PPM1G, PSMD8, RNF213, SLC25A3, UBA1, and WLS. We open source the implementation at: https://github.com/namnguyen0510/Biomarker-Discovery-with-Quantum-Neural-Networks .

Tubulin alpha-1b chain was identified as a prognosis and immune biomarker in pan-cancer combing with experimental validation in breast cancer

The α-tubulin subtype, Tubulin α-1b chain (TUBA1B), has been shown to influence immune cell infiltration, cancer growth, and survival across various malignancies. However, a comprehensive study has not yet been undertaken examining the immunological and predictive effects of TUBA1B in a pan-carcinoma context. Using data from TCGA, GEO, and other databases, we analyzed TUBA1B expression across various carcinoma types using transcriptional profiling, prognostic implications, genetic and epigenetic alterations, methylation patterns, and immunological significance. To validate our findings, we conducted Western blot analysis to assess TUBA1B protein levels in matched breast cancer tissue samples and performed CCK-8 proliferation assay, flow cytometry, transwell invasion, and migration assays to comprehensively examine the functional impact of TUBA1B on breast cancer cells. Our pan-cancer analysis found TUBA1B upregulation across most tumor types, with varying expression patterns in distinct immune and molecular subtypes. High TUBA1B expression was an independent risk factor and associated with poor prognoses in several cancers, including BRCA, KICH, LGG, LUAD, and MESO. TUBA1B also demonstrates moderate to high diagnostic accuracy in most tumor types. Increased m6A methylation levels were observed in the TUBA1B gene, while its promoter region displayed low methylation levels. TUBA1B's expression impacted some cancers by elevating tumor mutation burden, microsatellite instability, neoantigen formation, immune cell infiltration, and the modulation of immune checkpoints. Functional enrichment analysis highlights TUBA1B's involvement in important cellular processes such as the cell cycle, p53 signaling, cell senescence, programmed cell death, and the regulation of immune-related pathways. Moreover, our study reveals higher TUBA1B protein expression in breast cancer tissues compared to adjacent tissues. In vitro experiments confirm that TUBA1B deletion reduces breast cancer cell proliferation, invasion, and migration while increasing apoptosis. In conclusion, our study suggests that TUBA1B could potentially serve as a diagnostic marker for predicting cancer immunological profiles and survival outcomes and shed light on the expression and role of TUBA1B in breast cancer, providing a solid foundation for considering it as a promising therapeutic target for breast cancer patient treatment.

Molecular insights into clinical trials for immune checkpoint inhibitors in colorectal cancer: Unravelling challenges and future directions

Colorectal cancer (CRC) is a complex disease with diverse etiologies and clinical outcomes. Despite considerable progress in development of CRC therapeutics, challenges remain regarding the diagnosis and management of advanced stage metastatic CRC (mCRC). In particular, the five-year survival rate is very low since mCRC is currently rarely curable. Over the past decade, cancer treatment has significantly improved with the introduction of cancer immunotherapies, specifically immune checkpoint inhibitors. Therapies aimed at blocking immune checkpoints such as PD-1, PD-L1, and CTLA-4 target inhibitory pathways of the immune system, and thereby enhance anti-tumor immunity. These therapies thus have shown promising results in many clinical trials alone or in combination. The efficacy and safety of immunotherapy, either alone or in combination with CRC, have been investigated in several clinical trials. Clinical trials, including KEYNOTE-164 and CheckMate 142, have led to Food and Drug Administration approval of the PD-1 inhibitors pembrolizumab and nivolumab, respectively, for the treatment of patients with unresectable or metastatic microsatellite instability-high or deficient mismatch repair CRC. Unfortunately, these drugs benefit only a small percentage of patients, with the benefits of immunotherapy remaining elusive for the vast majority of CRC patients. To this end, primary and secondary resistance to immunotherapy remains a significant issue, and further research is necessary to optimize the use of immunotherapy in CRC and identify biomarkers to predict the response. This review provides a comprehensive overview of the clinical trials involving immune checkpoint inhibitors in CRC. The underlying rationale, challenges faced, and potential future steps to improve the prognosis and enhance the likelihood of successful trials in this field are discussed.

Agnostic Administration of Targeted Anticancer Drugs: Looking for a Balance between Hype and Caution

Many tumors have well-defined vulnerabilities, thus potentially allowing highly specific and effective treatment. There is a spectrum of actionable genetic alterations which are shared across various tumor types and, therefore, can be targeted by a given drug irrespective of tumor histology. Several agnostic drug-target matches have already been approved for clinical use, e.g., immune therapy for tumors with microsatellite instability (MSI) and/or high tumor mutation burden (TMB), NTRK1-3 and RET inhibitors for cancers carrying rearrangements in these kinases, and dabrafenib plus trametinib for BRAF V600E mutated malignancies. Multiple lines of evidence suggest that this histology-independent approach is also reasonable for tumors carrying ALK and ROS1 translocations, biallelic BRCA1/2 inactivation and/or homologous recombination deficiency (HRD), strong HER2 amplification/overexpression coupled with the absence of other MAPK pathway-activating mutations, etc. On the other hand, some well-known targets are not agnostic: for example, PD-L1 expression is predictive for the efficacy of PD-L1/PD1 inhibitors only in some but not all cancer types. Unfortunately, the individual probability of finding a druggable target in a given tumor is relatively low, even with the use of comprehensive next-generation sequencing (NGS) assays. Nevertheless, the rapidly growing utilization of NGS will significantly increase the number of patients with highly unusual or exceptionally rare tumor-target combinations. Clinical trials may provide only a framework for treatment attitudes, while the decisions for individual patients usually require case-by-case consideration of the probability of deriving benefit from agnostic versus standard therapy, drug availability, associated costs, and other circumstances. The existing format of data dissemination may not be optimal for agnostic cancer medicine, as conventional scientific journals are understandably biased towards the publication of positive findings and usually discourage the submission of case reports. Despite all the limitations and concerns, histology-independent drug-target matching is certainly feasible and, therefore, will be increasingly utilized in the future.

Identifying an immunogenic cell death-related gene signature contributes to predicting prognosis, immunotherapy efficacy, and tumor microenvironment of lung adenocarcinoma

BACKGROUND

Immunogenic cell death (ICD) is a regulated form of cell death that triggers an adaptive immune response. The objective of this study was to investigate the correlation between ICD-related genes (ICDGs) and the prognosis and the immune microenvironment of patients with lung adenocarcinoma (LUAD).

METHODS

ICD-associated molecular subtypes were identified through consensus clustering. Subsequently, a prognostic risk model comprising 5 ICDGs was constructed using Lasso-Cox regression in the TCGA training cohort and further tested in the GEO cohort. Enriched pathways among the subtypes were analyzed using GO, KEGG, and GSVA. Furthermore, the immune microenvironment was assessed using ESTIMATE, CIBERSORT, and ssGSEA analyses.

RESULTS

Consensus clustering divided LUAD patients into three ICDG subtypes with significant differences in prognosis and the immune microenvironment. A prognostic risk model was constructed based on 5 ICDGs and it was used to classify the patients into two risk groups; the high-risk group had poorer prognosis and an immunosuppressive microenvironment characterized by low immune score, low immune status, high abundance of immunosuppressive cells, and high expression of tumor purity. Cox regression, ROC curve analysis, and a nomogram indicated that the risk model was an independent prognostic factor. The five hub genes were verified by TCGA database, cell sublocalization immunofluorescence analysis, IHC images and qRT-PCR, which were consistent with bioinformatics analysis.

CONCLUSIONS

The molecular subtypes and a risk model based on ICDGs proposed in our study are both promising prognostic classifications in LUAD, which may provide novel insights for developing accurate targeted cancer therapies.

Identification of PPAR-related differentially expressed genes liver hepatocellular carcinoma and construction of a prognostic model based on data analysis and molecular docking

Liver hepatocellular carcinoma (LIHC) is a significant global health issue with limited treatment options. In this study, single-cell RNA sequencing (scRNA-seq) data were used to explore the molecular mechanisms of LIHC development and identify potential targets for therapy. The expression of peroxisome proliferator-activated receptors (PPAR)-related genes was analysed in LIHC samples, and primary cell populations, including natural killer cells, T cells, B cells, myeloid cells, endothelial cells, fibroblasts and hepatocytes, were identified. Analysis of the differentially expressed genes (DEGs) between normal and tumour tissues revealed significant changes in gene expression in various cell populations. PPAR activity was evaluated using the 'AUCell' R software, which indicated higher scores in the normal versus the malignant hepatocytes. Furthermore, the DEGs showed significant enrichment of pathways related to lipid and glucose metabolism, cell development, differentiation and inflammation. A prognostic model was then constructed using 8 PPARs-related genes, including FABP5, LPL, ACAA1, PPARD, FABP4, PLIN1, HMGCS2 and CYP7A1, identified using least absolute shrinkage and selection operator-Cox regression analysis, and validated in the TCGA-LIHC, ICGI-LIRI and GSE14520 datasets. Patients with low-risk scores had better prognosis in all cohorts. Based on the expression of the eight model genes, two clusters of patients were identified by ConsensusCluster analysis. We also predicted small-molecule drugs targeting the model genes, and identified perfluorohexanesulfonic acid, triflumizole and perfluorononanoic acid as potential candidates. Finally, wound healing assay confirmed that PPARD can promote the migration of liver cancer cells. Overall, our study offers novel perspectives on the molecular mechanisms of LIHC and potential areas for therapeutic intervention, which may facilitate the development of more effective treatment regimens.

Impact of the STK11/KRAS co-mutation on the response to immunotherapy in a real-world pan-cancer cohort

INTRODUCTION

Immune checkpoint inhibitors are highly effective in treating various cancers. We analyzed the significance of the KRAS/STK11 co-mutation in relation to the efficacy of immune checkpoint inhibitors in pan-cancer patient cohort.

METHODS

We analyzed data from open-access research: MSK-IMPACT (molecular profiling data from patients receiving systemic antitumor therapy) and MSK-TMB (molecular profiling data from patients receiving immune checkpoint inhibitors). In both studies, high throughput sequencing was used for molecular profiling.

RESULTS

A total of 10,336 patients receiving antitumor therapy (MSK-IMPACT study) and 1661 patients receiving immune checkpoint inhibitors (MSK-TMB study) were included in the analysis. Co-mutation STK11/KRAS was found in 156 (1.5%) and 46 (2.8%) patients in the two studies, respectively. Most patients with the STK11/KRAS co-mutation had non-small cell lung cancer (83% and 85% in the two studies, respectively). Among non-small cell lung cancer patients, the STK11 mutation was associated with a worse outcome for patients receiving systemic antitumor therapy, but not immune checkpoint inhibition therapy (HR for OS 1.90 [95% CI 1.36-2.65] and 1.44 [95% CI 0.88-2.37]). Co-mutation STK11/KRAS was also not associated with patient outcome in any of the studies (HR for OS 0.93 [95% CI 0.56-1.52] and 1.09 [95% CI 0.54-2.19]). High tumor mutational burden was associated with better outcome in the cohort of patients receiving immune checkpoint inhibitors. An analogous analysis among patients in the pan-cancer cohort (excluding patients with non-small cell lung cancer) showed STK11 mutations and high tumor mutational burden have a predictive role for the efficacy of immune checkpoint inhibitors, but not STK11/KRAS co-mutation.

CONCLUSIONS

Co-mutation STK11/KRAS is common among patients with non-small cell lung cancer and is not an independent predictive marker for the efficacy of immune checkpoint inhibitors. Further studies are required to clarify the role of STK11 mutations in immune checkpoint inhibitor treatment response.

Chromatin Remodelers Are Regulators of the Tumor Immune Microenvironment

Immune checkpoint inhibitors show remarkable responses in a wide range of cancers, yet patients develop adaptive resistance. This necessitates the identification of alternate therapies that synergize with immunotherapies. Epigenetic modifiers are potent mediators of tumor-intrinsic mechanisms and have been shown to regulate immune response genes, making them prime targets for therapeutic combinations with immune checkpoint inhibitors. Some success has been observed in early clinical studies that combined immunotherapy with agents targeting DNA methylation and histone modification; however, less is known about chromatin remodeler-targeted therapies. Here, we provide a discussion on the regulation of tumor immunogenicity by the chromatin remodeling SWI/SNF complex through multiple mechanisms associated with immunotherapy response that broadly include IFN signaling, DNA damage, mismatch repair, regulation of oncogenic programs, and polycomb-repressive complex antagonism. Context-dependent targeting of SWI/SNF subunits can elicit opportunities for synthetic lethality and reduce T-cell exhaustion. In summary, alongside the significance of SWI/SNF subunits in predicting immunotherapy outcomes, their ability to modulate the tumor immune landscape offers opportunities for therapeutic intervention.

GRIN2A mutation is a novel indicator of stratifying beneficiaries of immune checkpoint inhibitors in multiple cancers

Glutamate-NMDAR receptors (GRINs) have been reported to influence cancer immunogenicity; however, the relationship between GRIN alterations and the response to immune checkpoint inhibitors (ICIs) has not been determined. This study combined clinical characteristics and mutational profiles from multiple cohorts to form a discovery cohort (n = 901). The aim of this study was to investigate the correlation between the mutation status of the GRIN gene and the response to ICI therapy. Additionally, an independent ICI-treated cohort from the Memorial Sloan Kettering Cancer Center (MSKCC, N = 1513) was used for validation. Furthermore, this study explored the associations between GRIN2A mutations and intrinsic and extrinsic immunity using multiomics analysis. In the discovery cohort, patients with GRIN2A-MUTs had improved clinical outcomes, as indicated by a higher objective response rate (ORR: 36.8% vs 25.8%, P = 0.020), durable clinical benefit (DCB: 55.2% vs 38.7%, P = 0.005), prolonged progression-free survival (PFS: HR = 0.65; 95% CI 0.49 to 0.87; P = 0.003), and increased overall survival (OS: HR = 0.67; 95% CI 0.50 to 0.89; P = 0.006). Similar results were observed in the validation cohort, in which GRIN2A-MUT patients exhibited a significant improvement in overall survival (HR = 0.66; 95% CI = 0.49 to 0.88; P = 0.005; adjusted P = 0.045). Moreover, patients with GRIN2A-MUTs exhibited an increase in tumor mutational burden, high expression of costimulatory molecules, increased activity of antigen-processing machinery, and infiltration of various immune cells. Additionally, gene sets associated with cell cycle regulation and the interferon response were enriched in GRIN2A-mutated tumors. In conclusion, GRIN2A mutation is a novel biomarker associated with a favorable response to ICIs in multiple cancers.

Combining Genomic Biomarkers to Guide Immunotherapy in Non-Small Cell Lung Cancer

PURPOSE

The clinical value of STK11, KEAP1, and EGFR alterations for guiding immune checkpoint blockade (ICB) therapy in non-small cell lung cancer (NSCLC) remains controversial, as some patients with these proposed resistance biomarkers show durable ICB responses. More specific combinatorial biomarker approaches are urgently needed for this disease.

EXPERIMENTAL DESIGN

To develop a combinatorial biomarker strategy with increased specificity for ICB unresponsiveness in NSCLC, we performed a comprehensive analysis of 254 patients with NSCLC treated with ligand programmed death-ligand 1 (PD-L1) blockade monotherapy, including a discovery cohort of 75 patients subjected to whole-genome sequencing (WGS), and an independent validation cohort of 169 patients subjected to tumor-normal large panel sequencing. The specificity of STK11/KEAP1/EGFR alterations for ICB unresponsiveness was assessed in the contexts of a low (<10 muts/Mb) or high (≥10 muts/Mb) tumor mutational burden (TMB).

RESULTS

In low TMB cases, STK11/KEAP1/EGFR alterations were highly specific biomarkers for ICB resistance, with 0/15 (0.0%) and 1/34 (2.9%) biomarker-positive patients showing treatment benefit in the discovery and validation cohorts, respectively. This contrasted with high TMB cases, where 11/13 (85%) and 15/34 (44%) patients with at least one STK11/KEAP1/EGFR alteration showed durable treatment benefit in the discovery and validation cohorts, respectively. These findings were supported by analyses of progression-free survival and overall survival.

CONCLUSIONS

The unexpected ICB responses in patients carrying resistance biomarkers in STK11, KEAP1, and EGFR were almost exclusively observed in patients with a high TMB. Considering these alterations in context, the TMB offered a highly specific combinatorial biomarker strategy for limiting overtreatment in NSCLC.

Tumor Mutation Burden as a Cornerstone in Precision Oncology Landscapes: Effect of Panel Size and Uncertainty in Cutoffs

Tumor mutation burden (TMB) has profound implications for personalized cancer therapy, particularly immunotherapy. However, the size of the panel and the cutoff values for an accurate determination of TMB are still controversial. In this study, a pan-cancer analysis was performed on 22 cancer types from The Cancer Genome Atlas. The efficiency of gene panels of different sizes and the effect of cutoff values in accurate TMB determination was assessed on a large cohort using Whole Exome Sequencing data (n = 9929 patients) as the gold standard. Gene panels of four different sizes (i.e., 0.44-2.54 Mb) were selected for comparative analyses. The heterogeneity of TMB within and between cancer types is observed to be very high, and it becomes possible to obtain the exact TMB value as the size of the panel increases. In panels with limited size, it is particularly difficult to recognize patients with low TMB. In addition, the use of a general TMB cutoff can be quite misleading. The optimal cutoff value varies between 5 and 20, depending on the TMB distribution of the different tumor types. The use of comprehensive gene panels and the optimization of TMB cutoff values for different cancer types can make TMB a robust biomarker in precision oncology. Moreover, optimization of TMB can help accelerate translational medicine research, and by extension, delivery of personalized cancer care in the future.

Development of m6A/m5C/m1A regulated lncRNA signature for prognostic prediction, personalized immune intervention and drug selection in LUAD

Research indicates that there are links between m6A, m5C and m1A modifications and the development of different types of tumours. However, it is not yet clear if these modifications are involved in the prognosis of LUAD. The TCGA-LUAD dataset was used as for signature training, while the validation cohort was created by amalgamating publicly accessible GEO datasets including GSE29013, GSE30219, GSE31210, GSE37745 and GSE50081. The study focused on 33 genes that are regulated by m6A, m5C or m1A (mRG), which were used to form mRGs clusters and clusters of mRG differentially expressed genes clusters (mRG-DEG clusters). Our subsequent LASSO regression analysis trained the signature of m6A/m5C/m1A-related lncRNA (mRLncSig) using lncRNAs that exhibited differential expression among mRG-DEG clusters and had prognostic value. The model's accuracy underwent validation via Kaplan-Meier analysis, Cox regression, ROC analysis, tAUC evaluation, PCA examination and nomogram predictor validation. In evaluating the immunotherapeutic potential of the signature, we employed multiple bioinformatics algorithms and concepts through various analyses. These included seven newly developed immunoinformatic algorithms, as well as evaluations of TMB, TIDE and immune checkpoints. Additionally, we identified and validated promising agents that target the high-risk mRLncSig in LUAD. To validate the real-world expression pattern of mRLncSig, real-time PCR was carried out on human LUAD tissues. The signature's ability to perform in pan-cancer settings was also evaluated. The study created a 10-lncRNA signature, mRLncSig, which was validated to have prognostic power in the validation cohort. Real-time PCR was applied to verify the actual manifestation of each gene in the signature in the real world. Our immunotherapy analysis revealed an association between mRLncSig and immune status. mRLncSig was found to be closely linked to several checkpoints, such as IL10, IL2, CD40LG, SELP, BTLA and CD28, which could be appropriate immunotherapy targets for LUAD. Among the high-risk patients, our study identified 12 candidate drugs and verified gemcitabine as the most significant one that could target our signature and be effective in treating LUAD. Additionally, we discovered that some of the lncRNAs in mRLncSig could play a crucial role in certain cancer types, and thus, may require further attention in future studies. According to the findings of this study, the use of mRLncSig has the potential to aid in forecasting the prognosis of LUAD and could serve as a potential target for immunotherapy. Moreover, our signature may assist in identifying targets and therapeutic agents more effectively.

TET1 is a Diagnostic and Prognostic Biomarker Associated with Immune Infiltration in Papillary Thyroid Cancer

To investigate the function of ten-eleven translocation 1 (TET1) and its underlying mechanism in papillary thyroid cancer (PTC). Using the RNA-Seq data based on GDC TCGA, we analyzed the gene expression pattern of TET1 in PTC. Immunohistochemistry was carried out to assess the TET1 protein level. Then, its diagnostic and prognostic functions were determined by various bioinformatics approaches. Enrichment analysis was performed to explore the potential pathways in which TET1 is mainly involved. Finally, the immune cell infiltration analysis was conducted and the association of TET1 mRNA expression with the expression levels of immune checkpoints, tumor mutation burden (TMB) score, microsatellite instability (MSI) score, and cancer stem cells (CSC) score was examined. TET1 expression was lower in PTC tissues compared with that in normal tissues (P < 0.01). Besides, TET1 had a certain value in diagnosing PTC, and low-TET1 mRNA expression led to favorable disease-specific survival (DSS) (P < 0.01). The enrichment analysis revealed autoimmune thyroid disease and cytokine-cytokine receptor interaction were the consistent pathways in which TET1 participated. TET1 was negatively correlated with the Stromal score and Immune score. The different proportions of immune cell subtypes were observed between high- and low-TET1 expression groups. Interestingly, TET1 mRNA expression was inversely related to the expression levels of immune checkpoints, and TMB, MSI, and CSC scores. TET1 might be a robust diagnostic and prognostic biomarker for PTC. TET1 affected the DSS of PTC patients possibly through the regulation of immune-related pathways and tumor immunity.

How CLSPN could demystify its prognostic value and potential molecular mechanism for hepatocellular carcinoma: A crosstalk study

BACKGROUND & AIMS

CLSPN, a critical component of the S-phase checkpoint in response to DNA replication stress, has been implicated in the pathogenesis of multiple tumor types. The rising incidence of hepatocellular carcinoma (HCC) poses a significant challenge to global public health. Despite this, the specific functions of CLSPN in the development of HCC remain poorly understood.

METHODS

We systematically evaluated the expression of CLSPN, prognosis and immune infiltration in patients with HCC and identified a competing endogenous RNA (ceRNA) network by using public database. The RT-qPCR, western blot, CCK8, transwell, flow cytometry, animal experiments, proteasome inhibition experiment, Co-IP assay and mass spectrometry were applied to explore its biological functions, post-transcriptional modifications and potential molecular mechanisms of CLSPN in HCC.

RESULTS

We verified the expression of CLSPN, and its high expression is an independent prognostic factor in HCC. The expression of CLSPN is also associated with the immune microenvironment of HCC. CLSPN silencing inhibited the proliferation, migration, invasion and cell cycle progression of HCC cells. We established a PSMA3-AS1/hsa-miR-101-3p/CLSPN regulator axis in HCC. CLSPN was influenced by ubiquitination and was involved in the Wnt/β-catenin pathway to regulate HCC progression.

CONCLUSIONS

It was the first time to comprehensively discover and identify the expression, prognosis, immunotherapy, RNAs regulator, posttranscriptional modification, and molecular mechanisms of CLSPN in HCC. These novel insights have the potential to expedite the development of personalized treatment strategies and translational medicine approaches for HCC patients.

Adjuvant and neoadjuvant immunotherapies in hepatocellular carcinoma

Liver cancer, specifically hepatocellular carcinoma (HCC), is the sixth most common cancer and the third leading cause of cancer mortality worldwide. The development of effective systemic therapies, particularly those involving immune-checkpoint inhibitors (ICIs), has substantially improved the outcomes of patients with advanced-stage HCC. Approximately 30% of patients are diagnosed with early stage disease and currently receive potentially curative therapies, such as resection, liver transplantation or local ablation, which result in median overall survival durations beyond 60 months. Nonetheless, up to 70% of these patients will have disease recurrence within 5 years of resection or local ablation. To date, the results of randomized clinical trials testing adjuvant therapy in patients with HCC have been negative. This major unmet need has been addressed with the IMbrave 050 trial, demonstrating a recurrence-free survival benefit in patients with a high risk of relapse after resection or local ablation who received adjuvant atezolizumab plus bevacizumab. In parallel, studies testing neoadjuvant ICIs alone or in combination in patients with early stage disease have also reported efficacy. In this Review, we provide a comprehensive overview of the current approaches to manage patients with early stage HCC. We also describe the tumour immune microenvironment and the mechanisms of action of ICIs and cancer vaccines in this setting. Finally, we summarize the available evidence from phase II/III trials of neoadjuvant and adjuvant approaches and discuss emerging clinical trials, identification of biomarkers and clinical trial design considerations for future studies.

Personalized neoantigen vaccine and pembrolizumab in advanced hepatocellular carcinoma: a phase 1/2 trial

Programmed cell death protein 1 (PD-1) inhibitors have modest efficacy as a monotherapy in hepatocellular carcinoma (HCC). A personalized therapeutic cancer vaccine (PTCV) may enhance responses to PD-1 inhibitors through the induction of tumor-specific immunity. We present results from a single-arm, open-label, phase 1/2 study of a DNA plasmid PTCV (GNOS-PV02) encoding up to 40 neoantigens coadministered with plasmid-encoded interleukin-12 plus pembrolizumab in patients with advanced HCC previously treated with a multityrosine kinase inhibitor. Safety and immunogenicity were assessed as primary endpoints, and treatment efficacy and feasibility were evaluated as secondary endpoints. The most common treatment-related adverse events were injection-site reactions, observed in 15 of 36 (41.6%) patients. No dose-limiting toxicities or treatment-related grade ≥3 events were observed. The objective response rate (modified intention-to-treat) per Response Evaluation Criteria in Solid Tumors 1.1 was 30.6% (11 of 36 patients), with 8.3% (3 of 36) of patients achieving a complete response. Clinical responses were associated with the number of neoantigens encoded in the vaccine. Neoantigen-specific T cell responses were confirmed in 19 of 22 (86.4%) evaluable patients by enzyme-linked immunosorbent spot assays. Multiparametric cellular profiling revealed active, proliferative and cytolytic vaccine-specific CD4+ and CD8+ effector T cells. T cell receptor β-chain (TCRβ) bulk sequencing results demonstrated vaccination-enriched T cell clone expansion and tumor infiltration. Single-cell analysis revealed posttreatment T cell clonal expansion of cytotoxic T cell phenotypes. TCR complementarity-determining region cloning of expanded T cell clones in the tumors following vaccination confirmed reactivity against vaccine-encoded neoantigens. Our results support the PTCV's mechanism of action based on the induction of antitumor T cells and show that a PTCV plus pembrolizumab has clinical activity in advanced HCC. ClinicalTrials.gov identifier: NCT04251117 .

Established and emerging biomarkers of immunotherapy in renal cell carcinoma

Immunotherapies, such as immune checkpoint inhibitors, have heralded impressive progress for patient care in renal cell carcinoma (RCC). Despite this success, some patients' disease fails to respond, and other patients experience significant side effects. Thus, development of biomarkers is needed to ensure that patients can be selected to maximize benefit from immunotherapies. Improving clinicians' ability to predict which patients will respond to immunotherapy and which are most at risk of adverse events - namely through clinical biomarkers - is indispensable for patient safety and therapeutic efficacy. Accordingly, an evolving suite of therapeutic biomarkers continues to be investigated. This review discusses biomarkers for immunotherapy in RCC, highlighting current practices and emerging innovations, aiming to contribute to improved outcomes for patients with RCC.

Dynamics of The Γδtcr Repertoires During The Dedifferentiation Process and Pilot Implications for Immunotherapy of Thyroid Cancer

γδ T cells are evolutionarily conserved T lymphocytes that manifest unique antitumor efficacy independent of tumor mutation burden (TMB) and conventional human leukocyte antigen (HLA) recognition. However, the dynamic changes in their T cell receptor (TCR) repertoire during cancer progression and treatment courses remain unclear. Here, a comprehensive characterization of γδTCR repertoires are performed in thyroid cancers with divergent differentiation states through cross-sectional studies. The findings revealed a significant correlation between the differentiation states and TCR repertoire diversity. Notably, highly expanded clones are prominently enriched in γδ T cell compartment of dedifferentiated patients. Moreover, by longitudinal investigations of the γδ T cell response to various antitumor therapies, it is found that the emergence and expansion of the Vδ2neg subset may be potentially associated with favorable clinical outcomes after post-radiotherapeutic immunotherapy. These findings are further validated at single-cell resolution in both advanced thyroid cancer patients and a murine model, underlining the importance of further investigations into the role of γδTCR in cancer immunity and therapeutic strategies.

Who Should Receive Immunotherapy for Advanced Gastroesophageal Cancer?

OPINION STATEMENT

This paper shines a light on the exciting progress being made in using immunotherapy to treat advanced gastroesophageal cancers. The positive results from trials using drugs like Pembrolizumab and Nivolumab are certainly encouraging and open new possibilities for treating this challenging disease. However, it is clear that we still have a lot to learn about how to predict which patients will benefit most from these treatments. The exploration of combining therapies and using machine learning to guide treatment shows promise. Moving forward, it is crucial that researchers and healthcare professionals continue to work together, sharing knowledge and findings to continue the advancements in this important area.

Comprehensive analysis of disulfidptosis-related lncRNAs for predicting prognosis and response of immunotherapy in pancreatic adenocarcinoma

Background

Pancreatic adenocarcinoma (PAAD) is a common and deadly tumor. Currently, there is a severe lack of therapeutic options. As a novel mode of cell death, increasing evidence reveals the important role of the disulfidptosis in cancer. However, few studies have utilized disulfidptosis-related long-stranded non-coding RNAs (DRlncRNAs) to investigate the prognosis of PAAD.

Methods

We comprehensively analyzed the expression and prognostic value of 958 DRlncRNAs in PAAD using data from The Cancer Genome Atlas (TCGA). We established and validated a new DRlncRNAs-related prognostic index by least absolute shrinkage and selection operator (LASSO) and COX regression analysis. In addition, we built a nomogram consisting of risk score, age, gender, tumor grade and stage to validate the clinical feasibility of the index. We further evaluated the value of the index in terms of PAAD functional pathways, tumor microenvironment (TME) and tumor mutations.

Results

We designed a risk model for five DRlncRNAs and demonstrated its accuracy using receiver operating characteristic (ROC) curves. COX regression suggested that the model may be an independent predictor of cancer prognosis. Tumor immune infiltration analysis revealed that low-risk subgroups had higher extent of immune infiltration, higher sensitivity to immunotherapy and a higher TME score. This is helpful for us to discover more precise immunotherapy for PAAD patients.

Conclusions

In conclusion, we established a DRlncRNA index comprising of five DRlncRNAs, which may provide new insights for clinical diagnosis and precision therapy.

Comprehensive analysis of exosome gene LYPD3 and prognosis/immune cell infiltration in lung cancer

Background

Lung cancer (LC) is a leading cause of cancer-associated mortality worldwide, with high incidence and mortality rates. Ly6/PLAUR domain containing 3 (LYPD3) is a tumorigenic and highly glycosylated cell surface protein that has been rarely reported in LC. This study aimed to explore the prognostic role and immune cell infiltration of LYPD3 in LC.

Methods

We used ExoCarta, a database of exosomal proteins and RNA, to select exosomes in LC. The Tumor Immune Estimation Resource (TIMER) and Human Protein Atlas (HPA) databases were utilized to compare the expression of LYPD3 in LC. We applied Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and Kaplan-Meier (KM) plotter to evaluate the prognostic prediction performance of LYPD3. Biological processes (BPs), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and gene set enrichment analysis (GSEA) analyses were performed to illustrate the possible role of LYPD3 in LC. The correlations between LYPD3 and immune cell infiltration were explored using Tumor and Immune System Interaction Database (TISIDB), GEPIA2, and TIMER. R software was used for statistical analysis and mapping.

Results

A total of 904 exosome molecules were screened in LC. Further analysis showed that the up-regulation of LYPD3 in these 904 exosome molecules was associated with poor prognosis in LC. Pan-cancer analyses revealed that the expression of LYPD3 varied in many cancers, particularly in LC. Clinical correlation analysis indicated that LYPD3 was associated with stage and T classification in LC. We observed that LYPD3 co-expression genes were associated with cell cycle, DNA replication, proteasome, and regulation of the actin cytoskeleton by GSEA. Moreover, LYPD3 was associated with immune modulators. Immunophenoscores (IPS) and IPS-CTLA4 were significantly different between the high LYPD3 group and low LYPD3 group. Additionally, the median half maximal inhibitory concentration (IC50) of bexarotene, cyclopamine, etoposide, and paclitaxel in LYPD3 high group was significantly lower than that in LYPD3 low group.

Conclusions

LYPD3 is involved in many BPs of LC, such as regulating immune cell infiltration and affecting prognosis. Therefore, LYPD3 may have potential value as a biomarker for prognosis and immunotherapy in LC.

Identification of the Expression of TIE1 and Its Mediated Immunosuppression in Gastric Cancer

Background: Recently, various evidence has confirmed that Tyrosine Kinase with Immunoglobulin-like and EGF-like domains 1 (TIE1) promotes tumor growth in many cancers. However, the precise mechanism underlying TIE1's involvement in Gastric Cancer (GC) remains elusive. This research aimed to investigate the biological function of TIE1 in regulating GC progression. Methods: The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), GEPIA2.0, Sangerbox3.0 and TIMER databases were used to analyze the TIE1 expression. Immunohistochemistry (IHC) was used to demonstrate the expression of TIE1. TCGA, GEPIA2.0 and Kaplan-Meier were utilized for survival analysis and to explore the association of TIE1 with clinicopathological features. Protein-Protein Interaction (PPI) networks were constructed using Cytoscape. The potential molecular mechanism of TIE1 was investigated by Gene Ontology (GO), Kyoto Encyclopedia of Gene Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). We studied the relationships between TIE1 and mutations, immune checkpoints (ICs), tumor mutational burden (TMB), as well as microsatellite instability (MSI) to explore the underlying mechanism of immunity in GC. Results: Compared with normal tissue, TIE1 was significantly overexpressed in GC tissues (p = 0.0072) and was associated with poor survival (P < 0.05). According to GO and KEGG enrichment analyses, TIE1 was enriched in signal pathways related to the occurrence, invasion, and migration of malignant tumors (i.e., PI3K-Akt signaling pathway, Calcium signaling pathway, etc.). Immune infiltration analysis suggested that TIE1 is positively correlated with macrophages M2 and negatively correlated with Mast cells, naive B cells and Follicular helper T cells (TFH), which may be a contributing factor to tumor progression. Furthermore, the research on the tumor microenvironment (TME) and tumor purity also proved that TIE1 may be an oncogene. Mutation analysis showed that the high expression group of TIE1 had a higher frequency of mutations in TP53 and ARID1, while the TMB score was lower. Conclusion: TIE1 might be an oncogene via regulating dysregulated immune infiltration to cause immunosuppression in GC and could be identified as a biomarker for prognosis and a therapeutic target for GC.

RAC1 as a potential pan-cancer diagnostic, prognostic, and immunological biomarker

Background

Ras-related C3 botulinum toxin substrate 1 (RAC1) is an important member of the Rho GTPase family involved in tumorigenesis. However, its role and potential clinical utility across cancer entities in solid tumors is unknown.

Methods

We analyzed data from various databases, including The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression Project, cBioPortal, Tumor Immune Estimation Resource 2 (TIMER2), and published articles. A prognostic nomogram for liver hepatocellular carcinoma (LIHC) patients was developed based on RAC1-guanosine triphosphate (GTP) gene expression levels, which were validated using immunohistochemistry (IHC).

Results

In this study, RAC1 was highly expressed in most cancers and correlated with prognosis and pathological stages. Furthermore, significant associations were observed between RAC1 and DNA methylation, immune cell infiltration, immune-related genes, tumor mutational burden, and microsatellite instability in most tumors. As a use case, we employed gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) to analyze the biologic importance of RAC1 expression and established a prognostic nomogram based on tumor stage and RAC1 expression, which can better predict the overall survival rate of patients with LIHC better than tumor stage alone. The gene expression results were validated with IHC, which confirmed a higher expression of the RAC1-GTP protein in LIHC compared to paracancerous tissues.

Conclusions

This extensive solid tumor analysis provides sound evidence that RAC1 can serve as both as an immunotherapy target and as a diagnostic and prognostic biomarker.

Clinical variables associated with immune checkpoint inhibitor outcomes in patients with metastatic urothelial carcinoma: a multicentre retrospective cohort study

OBJECTIVES

Immune checkpoint inhibitors (ICIs) are indicated for metastatic urothelial cancer (mUC), but predictive and prognostic factors are lacking. We investigated clinical variables associated with ICI outcomes.

METHODS

We performed a multicentre retrospective cohort study of 135 patients who received ICI for mUC, 2016-2021, at three Canadian centres. Clinical characteristics, body mass index (BMI), metastatic sites, neutrophil-to-lymphocyte ratio (NLR), response and survival were abstracted from chart review.

RESULTS

We identified 135 patients and 62% had received ICI as a second-line or later treatment for mUC. A BMI ≥25 was significantly correlated to a higher overall response rate (ORR) (45.4% vs 16.3%, p value=0.020). Patients with BMI ≥30 experienced longer median overall survival (OS) of 24.8 vs 14.4 for 25≤BMI<30 and 8.5 months for BMI <25 (p value=0.012). The ORR was lower in the presence of bone metastases (16% vs 41%, p value=0.006) and liver metastases (16% vs 39%, p value=0.013). Metastatic lymph nodes were correlated with higher ORR (40% vs 20%, p value=0.032). The median OS for bone metastases was 7.3 versus 18 months (p value <0.001). Patients with liver metastases had a median OS of 8.6 versus 15 months (p value=0.006). No difference for lymph nodes metastases (13.5 vs 12.7 months, p value=0.175) was found. NLR ≥4 had worse OS (8.2 vs 17.7 months, p value=0.0001). In multivariate analysis, BMI ≥30, bone metastases, NLR ≥4, performance status ≥2 and line of ICI ≥2 were independent factors for OS.

CONCLUSIONS

Our data identified BMI and bone metastases as novel clinical biomarkers that were independently associated with ICI outcomes in mUC. External and prospective validation are warranted.