Tumor mutation burden for predicting immune checkpoint blockade response: the more, the better

Comparative analysis of non-coding and coding DNA mutations in flat urothelial lesions: biological implications and insights

Recent research in urothelial carcinoma (UC) has focused on coding mutations, leaving the significance of non-coding mutations unexplored. This study aims to evaluate non-coding DNA mutation frequencies compared to coding regions in normal urothelium and flat lesions, exploring their implications for tumor biology. Using targeted next-generation sequencing with UC-related gene panel, we analyzed non-coding and coding DNA mutation frequencies across 119 samples of flat urothelium encompassing various lesion types. Mutation patterns were examined based on the presence of associated flat or papillary tumors, and we investigated the correlation between mutation rates in target genes and genetic mutations within genomic regions. Intronic mutations (IMs) displayed variability across lesions, with normal urothelium (NU) exhibiting the highest frequency (43%) and urothelial carcinoma in situ (CIS) the lowest (9%). We observed similar sets of frequently mutated genes in both intronic and exonic regions, distinct from promoter region mutations. Although IMs paralleled exonic mutations in NU, reactive atypia, and atypia of unknown significance (AUS), they were less prevalent in dysplasia (DYS) and CIS. In contrast to CIS-associated AUS and DYS lesions, AUS-DYS lesions associated with papillary tumors exclusively exhibited recurrent intronic mutations involving FGFR3 and ERCC2, aligning with mutation patterns seen in exonic regions. ERCC2 intronic mutations correlated with the mutation rates of the gene panel. Our findings suggest that intronic mutations significantly contribute to tumor heterogeneity in urothelial lesions and may potentially be linked to genomic instability, warranting further investigation.

High tumor mutation burden mitigates the negative impact of chemotherapy history on immune checkpoint blockade therapy

Lung cancer remains the leading cause of cancer-related mortality worldwide, with non-small-cell lung cancer (NSCLC) accounting for the majority of cases. Immune checkpoint inhibitor (ICI) therapy, particularly with PD-1 inhibitors like nivolumab, has become a critical treatment option for advanced NSCLC. ICI therapy has revolutionized treatment, but prior chemotherapy may diminish ICI treatment efficacy. Tumor mutation burden (TMB) has emerged as a crucial predictor of ICI response, yet its interaction with chemotherapy history in ICI therapy is not fully understood. In this study, I investigate the impact of chemotherapy history on ICI treatment outcomes, focusing on TMB as a potential mitigating factor. Analyzing data from 512 patients with advanced NSCLC treated with PD-1/PD-L1 or CTLA-4 inhibitors, this sudy found that prior chemotherapy significantly reduced objective response rates (ORR) to ICI therapy, particularly in patients with low TMB (<15 mut/Mb). However, in patients with high TMB (≥15 mut/Mb), the negative impact of chemotherapy history on ICI treatment efficacy is minimal, suggesting that high TMB mitigates chemotherapy-induced resistance to ICI therapy. Furthermore, while chemotherapy history is associated with worse overall survival (OS) and progression-free survival (PFS) following ICI therapy in low-TMB patients, no such association is observed in high-TMB patients. These findings highlight the importance of TMB as a predictive biomarker, emphasizing the need for optimal treatment sequencing and personalized therapeutic strategies to overcome chemotherapy-induced immune resistance and maximize ICI treatment efficacy. These results suggest that ICI therapy may be more beneficial as a first-line treatment, particularly for patients with low TMB.

Comprehensive genetic variant analysis reveals combination of KRAS and LRP1B as a predictive biomarker of response to immunotherapy in patients with non-small cell lung cancer

BACKGROUND

In non-small cell lung cancer (NSCLC), the rapid advancement of predictive genetic testing of tumors by identifying specific pathogenic driver variants has significantly improved treatment guidance. However, immune checkpoint blockade (ICB) is typically administered to patients with tumors in the absence of such driver variants. Since only about 30% of patients will respond to ICB treatment, identifying novel genetic biomarkers of clinical response is crucial and will improve treatment decisions. This prospective clinical study aims to combine molecular biology, advanced bioinformatics and clinical data on response to treatment with ICB from a prospective cohort of NSCLC patients to identify single or combination of genetic variants in the tumor that can serve as predictive biomarkers of clinical response.

METHODS

In this prospective bi-center clinical study, we performed next-generation sequencing (NGS) of 597 cancer-associated genes in a prospective cohort of 49 patients as the final cohort analyzed, with stage III or IV NSCLC, followed by establishment of an in-house developed bioinformatics-based molecular classification method that integrates, interprets and evaluates data from multiple databases and variant prediction tools. Overall survival (OS) and progression-free survival (PFS) were analyzed for selected candidate genes and variants identified using our novel methodology including molecular tools, databases and clinical information.

RESULTS

Our novel molecular interpretation and classification method identified high impact variants in frequently altered genes KRAS, LRP1B, and TP53. Analysis of these genes as single predictive biomarkers in ICB-treated patients revealed that the presence of likely pathogenic variants and variants of unclear significance in LRP1B was associated with improved OS (p = 0.041). Importantly, further analysis of variant combinations in the tumor showed that co-occurrence of KRAS and LRP1B variants significantly improved OS (p = 0.003) and merged PFS (p = 0.008). Notably, the triple combination of variants in KRAS, LRP1B, and TP53 positively impacted both OS (p = 0.026) and merged PFS (p = 0.003).

CONCLUSIONS

This study suggests that combination of the LRP1B and KRAS variants identified through our novel molecular classification scheme leads to better outcomes following ICB treatment in NSCLC. The addition of TP53 improves the outcome even further. To our knowledge, this is the first report indicating that harboring a combination of KRAS, LRP1B, and TP53 variants can significantly enhance the response to ICB, suggesting a novel predictive biomarker combination for NSCLC patients.

Clinical metric of tumor mutational burden depicts colorectal cancer patients at the extremes

PURPOSE

Rare cases of colorectal cancer patients with exceptionally good or poor prognosis often remain overlooked, limiting insights into prognostic factors and underlying mechanisms.

METHODS

This study developed an analytical framework to investigate cancer patients at the extremes using tumor mutational burden (TMB). By analyzing data from 1277 colorectal cancer patients who did not receive immunotherapy, this analysis assessed how patient survival varies with a broad range of TMB levels.

RESULTS

Among patients with TMB ≤ 10 mutations per megabase (mut/Mb), increasing TMB was associated with worse survival outcomes. In contrast, patients with TMB > 10 mut/Mb showed  increasingly improved survival. Notably, a small subgroup (3.83%) with TMB > 60 mut/Mb had significantly better survival outcomes.

CONCLUSIONS

These findings highlight TMB's dual role in colorectal cancer progression. This study suggests that atypical patients can coexist within the same "disease continuum" with typical patients, under the universal context unified by a shared cancer hallmark. TMB provides a useful biomarker for identifying these extremes, offering a clinical metric to better predict patient outcomes and personalize treatment strategies.

The phenogenomic landscapes of pleural mesothelioma tumor microenvironment predict clinical outcomes

BACKGROUND

Malignant pleural mesothelioma (MPM) is a rare and aggressive malignancy with limited therapeutic options. To improve patients management and treatment, more precise stratification strategies are needed. This study aimed to characterize the phenogenomic landscapes of MPM and to understand their influence on patients clinical outcomes.

METHODS

We conducted a phenogenomic analysis on 22 MPM patients using two high throughput approaches: imaging mass cytometry (IMC) with whole exome sequencing (WES). Resulting profiles were addressed for their clinical relevance to predict patients prognosis.

RESULTS

IMC revealed a highly heterogeneous tumor microenvironment (TME) with distinct tumor cell subpopulations. Notably, we identified a novel sarcomatoid-like cellular cluster associated with poor prognosis. The TME was also infiltrated with immune cells including macrophages and CD4+ T lymphocytes, that were more abundant in patients with favorable clinical outcomes. WES identified a complex genomic landscape with limited prognostic value for individual genetic alterations. However, tumor mutational burden (TMB) emerged as a potential predictive biomarker, inversely correlating with immune cell infiltration, particularly macrophages and CD4+ T lymphocytes.

CONCLUSIONS

Our findings underscore the intricate interplay between the tumor genome, TME composition, and clinical outcomes in MPM. These data support the potential of integrating genomic and TME profiling to develop more precise patient stratification strategies and potentially optimize therapeutic approaches, including immunotherapy.

Skin mutation burden drives adaptive immunity and response to immunotherapy

Numerous studies over the past century have reported an inverse correlation between lifetime solar ultraviolet radiation (UV) exposure and all-cancer incidence and mortality. For decades, this relationship was hypothesized to reflect the action of photosynthesized vitamin D, though subsequent clinical trials have failed to demonstrate the expected anti-cancer properties. Rather than a consequence of vitamin D, I hypothesize that this inverse correlation reflects the immune stimulatory action of UV-derived skin neoantigens. Over time, such UV-mediated immune education drives immune repertoire diversification and superior adaptive immune responses to infectious disease and cancer. This hypothesis would explain the strong positive selection for light skin pigmentation following the out-of-Africa migration among humans inhabiting northerly latitude regions, and the longstanding racial disparities in cancer and infectious disease observed in North America. It suggests that the skin comprises an important reservoir of anti-cancer T cells that may be harnessed for anti-cancer therapy, and that skin mutation burden (SMB) may serve as a predictive biomarker of immunotherapy response. I propose a novel, non-invasive method for quantifying SMB as a biomarker.

A comprehensively prognostic and immunological analysis of PARP11 in pan-cancer

Poly (ADP-ribose) polymerase family member 11 (PARP11) has important immune regulatory functions in viral infection and tumor immune response. Particularly, PARP11 showed protumor activities in multiple preclinical murine models. However, no systematic pan-cancer analysis has been conducted to explore PARP11 function. In this study, we used multiple databases to assess PARP11 expression, which is associated with clinical outcomes, immune checkpoint factors, prognostic significance, genomic characteristics, and immunological aspects. The analysis revealed varying expression levels of PARP11 across different cancer types and a significant correlation between its expression and immune cell infiltration. Insights from the CellMiner database suggest a strong link between PARP11 expression and sensitivity to anticancer drugs, highlighting its potential as a therapeutic target. Moreover, PARP11 expression correlates with patient survival during anti-PD1 and anti-CTLA4 treatments, suggesting that PARP11 would be a predictor of immune checkpoint inhibitor treatment. In summary, PARP11 would be a potential immunoregulatory target and a diagnosis and prognosis marker for certain types of cancers. The detailed mechanisms of PARP11 in tumor immune responses need to be further investigated.

A landscape of checkpoint blockade resistance in cancer: underlying mechanisms and current strategies to overcome resistance

The discovery of immune checkpoints and the development of immune checkpoint inhibitors (ICI) have achieved a durable response in advanced-stage cancer patients. However, there is still a high proportion of patients who do not benefit from ICI therapy due to a lack of response when first treated (primary resistance) or detection of disease progression months after objective response is observed (acquired resistance). Here, we review the current FDA-approved ICI for the treatment of certain solid malignancies, evaluate the contrasting responses to checkpoint blockade in different cancer types, explore the known mechanisms associated with checkpoint blockade resistance (CBR), and assess current strategies in the field that seek to overcome these mechanisms. In order to improve current therapies and develop new ones, the immunotherapy field still has an unmet need in identifying other molecules that act as immune checkpoints, and uncovering other mechanisms that promote CBR.

Leveraging non-coding regions to guarantee the accuracy of small-sized panel-based tumor mutational burden estimates

Accurate estimation of tumor mutational burden (TMB) as a predictor of responsiveness to immune checkpoint inhibitors in gene panel assays requires an adequate panel size. The current calculations of TMB only consider coding regions, while most of gene panel assays interrogate non-coding regions. Leveraging the non-coding regions is a potential solution to address this panel size limitation. However, the impact of including non-coding regions on the accuracy of TMB estimates remains unclear. This study investigated the validity of leveraging non-coding regions to supplement panel size using the OncoGuide NCC Oncopanel System (NOP). The aim of this study was to evaluate test performance against orthogonal assays and the association with responsiveness to immune checkpoint inhibitors was not included in the evaluation. We compared TMB status and values between TMB calculated only from coding regions (NOP-coding) and from both coding and non-coding regions (NOP-overall) using whole exome sequencing (WES) and FoundationOne®CDx (F1CDx) assay. Our findings revealed that NOP-overall significantly improved the overall percent agreement (OPA) with TMB status compared with NOP-coding for both WES (OPA: 96.7% vs. 73.3%, n = 30) and F1CDx (OPA: 90.0% vs. 73.3%). Additionally, the mean difference in TMB values compared with WES was lower for NOP-overall (3.55 [95% CI: 0.98-6.13]) than for NOP-coding (6.22 [95% CI: 3.73-8.70]). These results exemplify the utility of incorporating non-coding regions to maintain accurate TMB estimates in small-sized panels.

The Role of Microsatellite Instability/DNA Mismatch Repair Deficiency and Tumor Mutational Burden as Biomarkers in Predicting Response to Immunotherapy in Castration-resistant Prostate Cancer

Large trials of immune checkpoint inhibitors (ICIs) in castration-resistant prostate cancer (CRPC) have mostly failed. Biomarker-selected CRPC patients, especially those with high microsatellite instability (MSI-H), mismatch repair deficiency (dMMR), or elevated tumor mutational burden (TMB), may benefit from single-agent ICIs. Despite their rarity in CRPC (∼2-5%), identification of MSI-H, dMMR, or TMB-H could improve patient selection for immunotherapy.

Harmonizing tumor mutational burden analysis: Insights from a multicenter study using in silico reference data sets in clinical whole-exome sequencing (WES)

OBJECTIVES

Tumor mutational burden (TMB) is a significant biomarker for predicting immune checkpoint inhibitor response, but the clinical performance of whole-exome sequencing (WES)-based TMB estimation has received less attention compared to panel-based methods. This study aimed to assess the reliability and comparability of WES-based TMB analysis among laboratories under routine testing conditions.

METHODS

A multicenter study was conducted involving 24 laboratories in China using in silico reference data sets. The accuracy and comparability of TMB estimation were evaluated using matched tumor-normal data sets. Factors such as accuracy of variant calls, limit of detection (LOD) of WES test, size of regions of interest (ROIs) used for TMB calculation, and TMB cutoff points were analyzed.

RESULTS

The laboratories consistently underestimated the expected TMB scores in matched tumor-normal samples, with only 50% falling within the ±30% TMB interval. Samples with low TMB score (<2.5) received the consensus interpretation. Accuracy of variant calls, LOD of the WES test, ROI, and TMB cutoff points were important factors causing interlaboratory deviations.

CONCLUSIONS

This study highlights real-world challenges in WES-based TMB analysis that need to be improved and optimized. This research will aid in the selection of more reasonable analytical procedures to minimize potential methodologic biases in estimating TMB in clinical exome sequencing tests. Harmonizing TMB estimation in clinical testing conditions is crucial for accurately evaluating patients' response to immunotherapy.

Integrated profile of tumor stage and mutational burden predicts disparate clinical responses to immune checkpoint inhibitors: A risk-benefit study

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, having demonstrated efficacy and leading to regulatory approvals of ICIs in cancers characterized by high tumor mutation burden (TMB). However, there remains a gap in determining their applicability and risk-benefit profile, across the broad spectrum of patients whose tumors harbor varying TMB levels across distinct tumor stages. By interrogating a large contemporary cohort comprised of 10,233 patients with a diagnosis of cancer across all tumor stages and TMB levels, this study revealed significantly improved overall survival (OS) following ICI therapy (P < .0001) in patients with a combination of ≥10 mut/Mb and stage IV disease. In contrast, ICI therapy is associated with markedly worse OS in patients with low TMB levels <10 mut/Mb and stages I, II, and III cancer. These findings highlight the critical interplay between TMB, tumor stage, and ICI treatment outcomes, underscoring the importance of integrating clinical and genetic characteristics in weighing the risk-benefit balance of ICI therapy. Although maximizing therapeutic benefits is crucial, it is equally important to identify and manage potential risks that may not be immediately apparent. This may require enrolling patients with less-severe or early-stage disease to enable long-term follow-up with effective clinical surveillance. By comprehensively evaluating the added benefit of improved treatment efficacy and the potential risk of adverse treatment outcome, a risk-benefit profile can optimize immunotherapy regimens, with profound implications for clinical decision-making and regulatory approvals of ICI.

Establishing a predictive model for tumor mutation burden status based on 18F-FDG PET/CT and clinical features of non-small cell lung cancer patients

Background

Tumor mutation burden (TMB) has emerged as a promising biomarker for immune checkpoint inhibitors (ICI) response, but its detection through whole exome sequencing (WES) is costly and invasive. This study aims to establish a predictive model for TMB using baseline metabolic parameters (MPs) of 18F-fluorodeoxyglucose (FDG) uptake on positron emission tomography/computed tomography (PET/CT) and clinical features in non-small cell lung cancer (NSCLC) patients, potentially offering a non-invasive and cost-effective method to predict TMB status.

Methods

A total of 223 NSCLC patients with baseline 18F-FDG PET/CT scans and TMB detection results were retrospectively enrolled from January 2019 to September 2023, and were divided into two groups: TMB-high (≥4 mutations/Mb, 96 patients) and TMB-low (<4 mutations/Mb, 127 patients). Twelve clinical features and five PET parameters were assessed. Univariate analysis was conducted in all patients to reveal the preliminary associations between variables and TMB status. All patients were randomly divided into a training set (n=135) and a validation set (n=88). Feature selection was performed using lasso regression and logistic regression analyses. A predictive model and nomogram were established with the features selected above. Decision curve analysis (DCA) was performed to assess the clinical utility of the developed model.

Results

Two clinical features and two PET parameters were identified through lasso regression and logistic regression analysis including pathology type, cancer antigen 125 (CA125) level, maximum standardized uptake value (SUVmax), and metabolic tumor volume (MTV). The predictive model exhibited an area under the curve (AUC) of 0.822 [95% confidence interval (CI), 0.751-0.894], and internal validation yielded an AUC of 0.822 (95% CI, 0.731-0.912). The model was well-calibrated. The developed nomogram, incorporating the four selected variables, showed promising potential in evaluating TMB status in NSCLC patients.

Conclusions

In this study, a predictive model combining 18F-FDG PET/CT and clinical features of NSCLC patients effectively distinguished between TMB-high and TMB-low status. The nomogram generated from this model holds significant promise for predicting TMB status, offering valuable insights for clinical decision-making.

TGFβ in Pancreas and Colorectal Cancer: Opportunities to Overcome Therapeutic Resistance

TGFβ is a pleiotropic signaling pathway that plays a pivotal role in regulating a multitude of cellular functions. TGFβ has a dual role in cell regulation where it induces growth inhibition and cell death; however, it can switch to a growth-promoting state under cancerous conditions. TGFβ is upregulated in colorectal cancer and pancreatic cancer, altering the tumor microenvironment and immune system and promoting a mesenchymal state. The upregulation of TGFβ in certain cancers leads to resistance to immunotherapy, and attempts to inhibit TGFβ expression have led to reduced therapeutic resistance when combined with chemotherapy and immunotherapy. Here, we review the current TGFβ inhibitor drugs in clinical trials for pancreatic and colorectal cancer, with the goal of uncovering advances in improving clinical efficacy for TGFβ combinational treatments in patients. Furthermore, we discuss the relevance of alterations in TGFβ signaling and germline variants in the context of personalizing treatment for patients who show lack of response to current therapeutics.

Combined cancer immunotherapy based on targeting adenosine pathway and PD-1/PDL-1 axis

INTRODUCTION

Cancer immunotherapy has revolutionized the field of oncology, offering new hope to patients with advanced malignancies. Tumor-induced immunosuppression limits the effectiveness of current immunotherapeutic strategies, such as PD-1/PDL-1 checkpoint inhibitors. Adenosine, a purine nucleoside molecule, is crucial to this immunosuppression because it stops T cells from activating and helps regulatory T cells grow. Targeting the adenosine pathway and blocking PD-1/PDL-1 is a potential way to boost the immune system's response to tumors.

AREAS COVERED

This review discusses the current understanding of the adenosine pathway in tumor immunology and the preclinical and clinical data supporting the combination of adenosine pathway inhibitors with PD-1/PDL-1 blockade. We also discuss the challenges and future directions for developing combination immunotherapy targeting the adenosine pathway and the PD-1/PDL-1 axis for cancer treatment.

EXPERT OPINION

The fact that the adenosine signaling pathway controls many immune system processes suggests that it has a wide range of therapeutic uses. Within the next five years, there will be tremendous progress in this area, and the standard of care for treating malignant tumors will have switched from point-to-point therapy to the integration of immunological networks comprised of multiple signaling pathways, like the adenosine axis.

Immunogenomic profiles and therapeutic options of the pan-programmed cell death-related lncRNA signature for patients with bladder cancer

Programmed cell death (PCD) is a process that eliminates infected, damaged, or possibly neoplastic cells to sustain homeostatic multicellular organisms. Although long noncoding RNAs (lncRNAs) are involved in various types of PCD and regulate tumor growth, invasion, and migration, the role of PCD-related lncRNAs in bladder cancer still lacks systematic exploration. In this research, we integrated multiple types of PCD as pan-PCD and identified eight pan-PCD-related lncRNAs (LINC00174, HCP5, HCG27, UCA1, SNHG15, GHRLOS, CYB561D2, and AGAP11). Then, we generated a pan-PCD-related lncRNA prognostic signature (PPlncPS) with excellent predictive power and reliability, which performed equally well in the E-MTAB-4321 cohort. In comparison with the low-PPlncPS score group, the high-PPlncPS score group had remarkably higher levels of angiogenesis, matrix, cancer-associated fibroblasts, myeloid cell traffic, and protumor cytokine signatures. In addition, the low-PPlncPS score group was positively correlated with relatively abundant immune cell infiltration, upregulated expression levels of immune checkpoints, and high tumor mutation burden (TMB). Immunogenomic profiles revealed that patients with both low PPlncPS scores and high TMB had the best prognosis and may benefit from immune checkpoint inhibitors. Furthermore, for patients with high PPlncPS scores, docetaxel, staurosporine, and luminespib were screened as potential therapeutic candidates. In conclusion, we generated a pan-PCD-related lncRNA signature, providing precise and individualized prediction for clinical prognosis and some new insights into chemotherapy and immune checkpoint inhibitor therapy for bladder cancer.

Exploring Predictive and Prognostic Biomarkers in Colorectal Cancer: A Comprehensive Review

Colorectal cancer (CRC) remains the second leading cause of cancer-related mortality worldwide. While immune checkpoint inhibitors have significantly improved patient outcomes, their effectiveness is mostly limited to tumors with microsatellite instability (MSI-H/dMMR) or an increased tumor mutational burden, which comprise 10% of cases. Advancing personalized medicine in CRC hinges on identifying predictive biomarkers to guide treatment decisions. This comprehensive review examines established tissue markers such as KRAS and HER2, highlighting their roles in resistance to anti-EGFR agents and discussing advances in targeted therapies for these markers. Additionally, this review summarizes encouraging data on promising therapeutic targets and highlights the clinical utility of liquid biopsies. By synthesizing current evidence and identifying knowledge gaps, this review provides clinicians and researchers with a contemporary understanding of the biomarker landscape in CRC. Finally, the review examines future directions and challenges in translating promising biomarkers into clinical practice, with the goal of enhancing personalized medicine approaches for colorectal cancer patients.

SPP1 could be an immunological and prognostic biomarker: From pan-cancer comprehensive analysis to osteosarcoma validation

Secreted phosphoprotein 1 (SPP1), also known as osteopontin, is a phosphorylated protein. High SPP1 expression levels have been detected in multiple cancers and are associated with poor prognosis and reduced survival rates. However, only a few pan-cancer analyses have targeted SPP1. We conducted a comprehensive analysis using multiple public databases, including TIMER and TCGA, to investigate the expression levels of SPP1 in 33 different tumor types. In addition, we verified the effect of SPP1 on osteosarcoma. To assess the impact of SPP1 on patient outcomes, we employed univariate Cox regression and Kaplan-Meier survival analyses to analyze overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in these tumor patients. We also explored SPP1 gene alterations in various tumor tissues using cBioPortal. We then examined the relationship between SPP1 and clinical characteristics, TME, immune regulatory genes, immune checkpoints, TMB, and MSI using R language. In addition, we used GSEA to investigate the molecular mechanisms underlying the role of SPP1. Bioinformatics analysis indicated that SPP1 was upregulated in 17 tumors. Overexpression of SPP1 results in poor OS, DSS, and PFI in CESC, ESCA, GBM, LGG, LIHC, PAAD, PRAD, and skin cutaneous melanoma. SPP1 expression was positively associated with immunocyte infiltration, immune regulatory genes, immune checkpoints, TMB, MSI, and drug sensitivity in certain cancers. We found that high expression of SPP1 in osteosarcoma was related to drug resistance and metastasis and further demonstrated that SPP1 can stimulate osteosarcoma cell proliferation via CCND1 by activating the PI3K/Akt pathway. These findings strongly suggest that SPP1 is a potential prognostic marker and novel target for cancer immunotherapy.

Immunotherapy and radiotherapy for older patients with invasive bladder cancer unfit for surgery or chemotherapy: practical proposal by the international geriatric radiotherapy group

The standard of care for non-metastatic muscle invasive bladder cancer is either radical cystectomy or bladder preservation therapy, which consists of maximal transurethral bladder resection of the tumor followed by concurrent chemoradiation with a cisplatin-based regimen. However, for older cancer patients who are too frail for surgical resection or have decreased renal function, radiotherapy alone may offer palliation. Recently, immunotherapy with immune checkpoint inhibitors (ICI) has emerged as a promising treatment when combined with radiotherapy due to the synergy of those two modalities. Transitional carcinoma of the bladder is traditionally a model for immunotherapy with an excellent response to Bacille Calmette-Guerin (BCG) in early disease stages, and with avelumab and atezolizumab for metastatic disease. Thus, we propose an algorithm combining immunotherapy and radiotherapy for older patients with locally advanced muscle-invasive bladder cancer who are not candidates for cisplatin-based chemotherapy and surgery.

Enhancing antitumor efficacy of oncolytic virus M1 via albendazole-sustained CD8+ T cell activation

The immune response plays a crucial role in the functionality of oncolytic viruses. In this study, Albendazole, an antihelminthic drug known to modulate the immune checkpoint PD-L1, was combined with the oncolytic virus M1 (OVM1) to treat mice with either prostate cancer (RM-1) or glioma (GL261) tumors. This combination therapy enhanced anti-tumor effects in immunocompetent mice, but not in immunodeficient ones, without increasing OVM1 replication. Instead, it led to an increase in the number of CD8+ T cells within the tumor, downregulated the expression of PD1 on CD8+ T cells, and upregulated activation markers such as Ki67, CD44, and CD69 and the secretion of cytotoxic factors including interferon (IFN)-γ, granzyme B, and tumor necrosis factor (TNF)-α. Consistently, it enhanced the in vitro tumor-killing activity of lymphocytes from tumor-draining lymph nodes or spleens. The synergistic effect of Albendazole on OVM1 was abolished by depleting CD8+ T cells, suggesting a CD8+ T cell-dependent mechanism. In addition, Albendazole and OVM1 therapy increased CTLA4 expression in the spleen, and the addition of CTLA4 antibodies further enhanced the anti-tumor efficacy in vivo. In summary, Albendazole can act synergistically with oncolytic viruses via CD8+ T cell activation, and the Albendazole/OVM1 combination can overcome resistance to CTLA4-based immune checkpoint blockade therapy.

Development of Traceable Mouse Models of Advanced and Metastatic Bladder Cancer

Bladder cancer (BC) is the fourth most common cancer in men, with a poor patient prognosis for advanced disease. The poor survival of patients with muscle-invasive bladder cancer (MIBC) and metastatic status emphasizes the urgent need to develop new therapies. Lacking in the field of BC is the availability of relevant advanced BC mouse models, especially metastatic ones, that accurately recapitulate the complexities of human pathology to test and study new therapeutic strategies. Addressing this need, we developed a traceable mouse model of BC that expresses tumor-associated antigens within the context of advanced muscle-invasive BC. This novel system was achieved through the deletion of the tp53 and pten genes, alongside the incorporation of the fusion construct of Firefly luciferase (Luc) and the SIYRYYGL (SIY) T-cell antigen. We validate that the presence of the transgene did not impact on the development of the tumors while allowing us to measure tumor progression by bioluminescence. We show that the transgene did not influence the composition of the immune tumor microenvironment. More importantly, we report that this model was unresponsive to anti-PD-1 treatment, as in the majority of patients with BC. We also develop a new model based on the orthotopic injection of BC clonal cell lines derived from our first model. We demonstrate that this new model invades the muscle layer and has a metastasis development rate of 83%. The advantage of this model is that we can visualize tumor growth and metastasis development in vivo. These mouse models' characteristics, displaying many similarities with the human pathology, provide a valuable tool for tracking tumor progression, metastasis spread in vivo, and treatment resistance, as well as exploring fundamental and translational aspects of BC biology. This work contributes to the improvement in the landscape of mouse models of advanced BC for testing new therapeutic strategies.

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.

Comprehensive analysis and prognostic assessment of senescence-associated genes in bladder cancer

BACKGROUND

The prevalence and mortality of bladder cancer (BLCA) present a significant medical challenge. While the function of senescence-related genes in tumor development is recognized, their prognostic significance in BLCA has not been thoroughly explored.

METHODS

BLCA transcriptome datasets were sourced from the TCGA and GEO repositories. Gene groupings were determined through differential gene expression and non-negative matrix factorization (NMF) methodologies. Key senescence-linked genes were isolated using singular and multivariate Cox regression analyses, combined with lasso regression. Validation was undertaken with GEO database information. Predictive models, or nomograms, were developed by merging risk metrics with clinical records, and their efficacy was gauged using ROC curve methodologies. The immune response's dependency on the risk metric was assessed through the immune phenomenon score (IPS). Additionally, we estimated IC50 metrics for potential chemotherapeutic agents.

RESULTS

Reviewing 406 neoplastic and 19 standard tissue specimens from the TCGA repository facilitated the bifurcation of subjects into two unique clusters (C1 and C2) according to senescence-related gene expression. After a stringent statistical evaluation, a set of ten pivotal genes was discerned and applied for risk stratification. Validity tests for the devised nomograms in forecasting 1, 3, and 5-year survival probabilities for BLCA patients were executed via ROC and calibration plots. IC50 estimations highlighted a heightened responsiveness in the low-risk category to agents like cisplatin, cyclopamine, and sorafenib.

CONCLUSIONS

In summation, our research emphasizes the prospective utility of risk assessments rooted in senescence-related gene signatures for enhancing BLCA clinical oversight.

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.

Case report: Temozolomide induced hypermutation indicates an unfavorable response to immunotherapy in patient with gliomas

Background

Temozolomide (TMZ) is a key component in the treatment of gliomas. Hypermutation induced by TMZ can be encountered in routine clinical practice, and its significance is progressively gaining recognition. However, the relationship between TMZ-induced hypermutation and the immunologic response remains controversial.

Case presentation

We present the case of a 38-year-old male patient who underwent five surgeries for glioma. Initially diagnosed with IDH-mutant astrocytoma (WHO grade 2) during the first two surgeries, the disease progressed to grade 4 in subsequent interventions. Prior to the fourth surgery, the patient received 3 cycles of standard TMZ chemotherapy and 9 cycles of dose-dense TMZ regimens. Genomic and immunologic analyses of the tumor tissue obtained during the fourth surgery revealed a relatively favorable immune microenvironment, as indicated by an immunophenoscore of 5, suggesting potential benefits from immunotherapy. Consequently, the patient underwent low-dose irradiation combined with immunoadjuvant treatment. After completing 4 cycles of immunotherapy, the tumor significantly shrank, resulting in a partial response. However, after a 6-month duration of response, the patient experienced disease progression. Subsequent analysis of the tumor tissue obtained during the fifth surgery revealed the occurrence of hypermutation, with mutation signature analysis attributing TMZ treatment as the primary cause. Unfortunately, the patient succumbed shortly thereafter, with a survival period of 126 months.

Conclusion

Patients subjected to a prolonged regimen of TMZ treatment may exhibit heightened vulnerability to hypermutation. This hypermutation induced by TMZ holds the potential to function as an indicator associated with unfavorable response to immunotherapy in gliomas.

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.

PIK3CA mutation-driven immune signature as a prognostic marker for evaluating the tumor immune microenvironment and therapeutic response in breast cancer

PURPOSE

Gene mutations drive tumor immune microenvironment (TIME) heterogeneity, in turn affecting prognosis and immunotherapy efficacy. PIK3CA is the most frequently mutated gene in breast cancer (BC), yet its relevance to BC prognosis remains controversial. Herein, we sought to determine the impact of PIK3CA mutation-driven immune genes (PDIGs) on BC prognosis in relation to TIME heterogeneity.

METHODS

PIK3CA mutation characteristics were compared and verified between the TCGA-BRCA dataset and a patient cohort from our hospital. PIK3CA mutation-driven differentially expressed genes were identified for consensus clustering and weighted gene co-expression network analysis to select the modules most relevant to the immune subtype. Thereafter, the two were intersected to obtain PDIGs. Univariate Cox, LASSO, and multivariate Cox regression analyses were sequentially performed on PDIGs to obtain a PIK3CA mutation-driven immune signature (PDIS), which was then validated using the Gene Expression Omnibus (GEO) database. Differences in functional enrichment, mutation landscape, immune infiltration, checkpoint gene expression, and drug response were compared between different risk groups.

RESULTS

PIK3CA mutation frequencies in the TCGA and validation cohorts were 34.49% and 40.83%, respectively. PIK3CA mutants were significantly associated with ER, PR, and molecular BC subtypes in our hospital cohort. The PDIS allowed for effective risk stratification and exhibited prognostic power in TCGA and GEO sets. The low-risk patients exhibited greater immune infiltration, higher expression of common immune checkpoint factors, and lower scores for tumor immune dysfunction and exclusion.

CONCLUSION

The PDIS can be used as an effective prognostic model for predicting immunotherapy response to guide clinical decision-making.

Enhancing the quality of panel-based tumor mutation burden assessment: a comprehensive study of real-world and in-silico outcomes

Targeted panel-based tumor mutation burden (TMB) assays are widely employed to guide immunotherapy for patients with solid tumors. However, the accuracy and consistency of this method can be compromised due to the variability in technical details across different laboratories, particularly in terms of panel size, somatic mutation detection and TMB calculation rules. Currently, systematic evaluations of the impact of these technical factors on existing assays and best practice recommendations remain lacking. We assessed the performance of 50 participating panel-based TMB assays involving 38 unique methods using cell line samples. In silico experiments utilizing TCGA MC3 datasets were performed to further dissect the impact of technical factors. Here we show that the panel sizes beyond 1.04 Mb and 389 genes are necessary for the basic discrete accuracy, as determined by over 40,000 synthetic panels. The somatic mutation detection should maintain a reciprocal gap of recall and precision less than 0.179 for reliable psTMB calculation results. The inclusion of synonymous, nonsense and hotspot mutations could enhance the accuracy of panel-based TMB assay. A 5% variant allele frequency cut-off is suitable for TMB assays using tumor samples with at least 20% tumor purity. In conclusion, this multicenter study elucidates the major technical factors as sources of variability in panel-based TMB assays and proposed comprehensive recommendations for the enhancement of accuracy and consistency. These findings will assist clinical laboratories in optimizing the methodological details through bioinformatic experiments to enhance the reliability of panel-based methods.

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-Exome Sequencing Identifies Mutation Profile and Mutation Signature-Based Clustering Associated with Prognosis in Appendiceal Pseudomyxoma Peritonei

Pseudomyxoma peritonei (PMP) is a rare malignant clinical syndrome with little known about the global mutation profile. In this study, whole-exome sequencing (WES) was performed in 49 appendiceal PMP to investigate mutation profiles and mutation signatures. A total of 4,020 somatic mutations were detected, with a median mutation number of 56 (1-402). Tumor mutation burden (TMB) was generally low (median 1.55 mutations/Mb, 0.12-11.26 mutations/Mb). Mutations were mainly enriched in the function of cancer-related axonogenesis, extracellular matrix-related processes, calcium signaling pathway, and cAMP signaling pathway. Mutations in FCGBP, RBFOX1, SPEG, RTK-RAS, PI3K-AKT, and focal adhesion pathways were associated with high-grade mucinous carcinoma peritonei. These findings revealed distinct mutation profile in appendiceal PMP. Ten mutation signatures were identified, dividing patients into mutation signature cluster (MSC) 1 (N = 28, 57.1%) and MSC 2 (N = 21, 42.9%) groups. MSC (P = 0.007) was one of the four independent factors associated with 3-year survival. TMB (P = 0.003) and microsatellite instability (P = 0.002) were independent factors associated with MSC 2 grouping. Taken together, our findings provided a broader view in the understanding of molecular pathologic mechanism in appendiceal PMP and may be critical to developing an individualized approach to appendiceal PMP treatment.

IMPLICATIONS

This work describes exhaustive mutation profile of PMP based on WES data and derives ten mutation signatures, which divides patients into two clusters and serve as an independent prognostic factor associated with 3-year survival.

Pathways to hypermutation in high-grade gliomas: Mechanisms, syndromes, and opportunities for immunotherapy

Despite rapid advances in the field of immunotherapy, including the success of immune checkpoint inhibition in treating multiple cancer types, clinical response in high-grade gliomas (HGGs) has been disappointing. This has been in part attributed to the low tumor mutational burden (TMB) of the majority of HGGs. Hypermutation is a recently characterized glioma signature that occurs in a small subset of cases, which may open an avenue to immunotherapy. The substantially elevated TMB of these tumors most commonly results from alterations in the DNA mismatch repair pathway in the setting of extensive exposure to temozolomide or, less frequently, from inherited cancer predisposition syndromes. In this review, we discuss the genetics and etiology of hypermutation in HGGs, with an emphasis on the resulting genomic signatures, and the state and future directions of immuno-oncology research in these patient populations.

Restriction site associated DNA sequencing for tumour mutation burden estimation and mutation signature analysis

BACKGROUND

Genome-wide measures of genetic disruption such as tumour mutation burden (TMB) and mutation signatures are emerging as useful biomarkers to stratify patients for treatment. Clinicians commonly use cancer gene panels for tumour mutation burden estimation, and whole genome sequencing is the gold standard for mutation signature analysis. However, the accuracy and cost associated with these assays limits their utility at scale.

METHODS

WGS data from 560 breast cancer patients was used for in silico library simulations to evaluate the accuracy of an FDA approved cancer gene panel as well as restriction enzyme associated DNA sequencing (RADseq) libraries for TMB estimation and mutation signature analysis. We also transfected a mouse mammary cell line with APOBEC enzymes and sequenced resulting clones to evaluate the efficacy of RADseq in an experimental setting.

RESULTS

RADseq had improved accuracy of TMB estimation and derivation of mutation profiles when compared to the FDA approved cancer panel. Using simulated immune checkpoint blockade (ICB) trials, we show that inaccurate TMB estimation leads to a reduction in power for deriving an optimal TMB cutoff to stratify patients for immune checkpoint blockade treatment. Additionally, prioritisation of APOBEC hypermutated tumours in these trials optimises TMB cutoff determination for breast cancer. The utility of RADseq in an experimental setting was also demonstrated, based on characterisation of an APOBEC mutation signature in an APOBEC3A transfected mouse cell line.

CONCLUSION

In conclusion, our work demonstrates that RADseq has the potential to be used as a cost-effective, accurate solution for TMB estimation and mutation signature analysis by both clinicians and basic researchers.

Immunotherapy-related biomarkers: Confirmations and uncertainties

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

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.

Utility of Tumor Mutational Burden as a Biomarker for Response to Immune Checkpoint Inhibition in the VA Population

PURPOSE

Immune checkpoint inhibitors (ICIs) are used for an increasing number of indications across various tumor types, as well as several tumor-agnostic indications in patients with advanced cancer. Although many patients benefit from ICI therapy, others do not, highlighting a need for better predictive biomarkers. Tumor mutational burden (TMB) reflects the global number of mutations within a tumor and has been widely explored as a predictive biomarker of ICI response. The current tumor type-agnostic US Food and Drug Administration approval of pembrolizumab for metastatic solid tumors defines high TMB (TMB-H) as ≥10 mut/Mb as measured by FoundationOne CDx. This fixed cutoff may not be the ideal value across all solid tumors.

METHODS

We performed a retrospective analysis of the association of survival outcomes with TMB in patients treated with ICI for five major cancer types, using real-world data from the VA. Survival was measured from initiation of ICI, and Kaplan-Meier survival curves were compared by log-rank test.

RESULTS

Overall survival (OS) was significantly longer for patients with TMB-H versus TMB low tumors in non-small-cell lung cancer (NSCLC; n = 1,593), head and neck (H&N) cancer (n = 222), and urothelial cancer (n = 332). OS was not significantly different based on TMB status in melanoma (n = 207) or esophageal/gastric cancer (n = 248).

CONCLUSION

Consistent with previous studies, a predictive value of TMB ≥10 mut/Mb for ICI response was found in NSCLC and H&N, but not in esophageal/gastric cancer. Although inconclusive in the literature, significant association was found in urothelial cancer. The predictive value of TMB in melanoma was inconclusive. Our analysis does not support the use of a fixed threshold for TMB as a standalone predictive biomarker for ICI across all solid tumors.

Fibroblast growth factor receptor 3 mutation attenuates response to immune checkpoint blockade in metastatic urothelial carcinoma by driving immunosuppressive microenvironment

BACKGROUND

Immune checkpoint blockade (ICB) therapy holds promise in metastatic urothelial carcinoma (UC). Fibroblast growth factor receptor 3 (FGFR3) mutation drives T-cell-depleted microenvironment in UC, which led to the hypothesis that FGFR3 mutation might attenuate response to ICB in patients with metastatic UC. The study aims to compare prognosis and response between patients with FGFR3-mutated and FGFR3-wildtype metastatic UC after ICB therapy, and decode the potential molecular mechanisms.

METHODS

Based on the single-arm, multicenter, phase 2 trial, IMvigor210, we conducted a propensity score matched (PSM) analysis. After a 1:1 ratio PSM method, 39 patients with FGFR3-mutated and 39 FGFR3-wildtype metastatic UC treated with atezolizumab were enrolled. A meta-analysis through systematical database retrieval was conducted for validation. In addition, we performed single-cell RNA sequencing on three FGFR3-mutated and three FGFR3-wildtype UC tumors and analyzed 58,069 single cells.

RESULTS

The PSM analysis indicated FGFR3-mutated patients had worse overall survival (OS) in comparison to FGFR3-wildtype patients (HR=2.11, 95% CI=(1.16 to 3.85), p=0.015) receiving atezolizumab. The median OS was 9.2 months (FGFR3-mutated) versus 21.0 months (FGFR3-wildtype). FGFR3-mutated patients had lower disease control rate than FGFR3-wildtype patients (41.0% vs 66.7%, p=0.023). The meta-analysis involving 938 patients with metastatic UC confirmed FGFR3 mutation was associated with worse OS after ICB (HR=1.28, 95% CI=(1.04 to 1.59), p=0.02). Single-cell RNA transcriptome analysis identified FGFR3-mutated UC carried a stronger immunosuppressive microenvironment compared with FGFR3-wildtype UC. FGFR3-mutated UC exhibited less immune infiltration, and lower T-cell cytotoxicity. Higher TREM2+ macrophage abundance in FGFR3-mutated UC can undermine and suppress the T cells, potentially contributing to the formation of an immunosuppressive microenvironment. Lower inflammatory-cancer-associated fibroblasts in FGFR3-mutated UC recruited less chemokines in antitumor immunity but expressed growth factors to promote FGFR3-mutated malignant cell development. FGFR3-mutated UC carried abundance of malignant cells characterized by high hypoxia/metabolism and low interferon response phenotype.

CONCLUSIONS

FGFR3 mutation can attenuate prognosis and response to ICB in patients with metastatic UC. FGFR3-mutated UC carries a stronger immunosuppressive microenvironment in comparison with FGFR3-wildtype UC. Inhibition of FGFR3 might activate the immune microenvironment, and the combination of FGFR inhibitor targeted therapy and ICB might be a promising therapeutic regimen in metastatic UC, providing important implications for UC clinical management.

Rheumatic complications of checkpoint inhibitors: Lessons from autoimmunity

Immune checkpoint inhibitors are now an established treatment in the management of a range of cancers. Their success means that their use is likely to increase in future in terms of the numbers of patients treated, the indications and the range of immune checkpoints targeted. They function by counteracting immune evasion by the tumor but, as a consequence, can breach self-tolerance at other sites leading to a range of immune-related adverse events. Included among these complications are a range of rheumatologic complications, including inflammatory arthritis and keratoconjunctivitis sicca. These superficially resemble immune-mediated rheumatic diseases (IMRDs) such as rheumatoid arthritis and Sjogren's disease but preliminary studies suggest they are clinically and immunologically distinct entities. However, there appear to be common processes that predispose to the development of both that may inform preventative interventions and predictive tools. Both groups of conditions highlight the centrality of immune checkpoints in controlling tolerance and how it can be restored. Here we will discuss some of these commonalities and differences between rheumatic irAEs and IMRDs.

Identification of molecular subtypes based on PANoptosis-related genes and construction of a signature for predicting the prognosis and response to immunotherapy response in hepatocellular carcinoma

Background

Previous studies have demonstrated that PANoptosis is strongly correlated with cancer immunity and progression. This study aimed to develop a PANoptosis-related signature (PANRS) to explore its potential value in predicting the prognosis and immunotherapy response of hepatocellular carcinoma (HCC).

Methods

Based on the expression of PANoptosis-related genes, three molecular subtypes were identified. To construct a signature, the differentially expressed genes between different molecular subtypes were subjected to multivariate least absolute shrinkage and selection operator Cox regression analyses. The risk scores of patients in the training set were calculated using the signature. The patients were classified into high-risk and low-risk groups based on the median risk scores. The predictive performance of the signature was evaluated using Kaplan-Meier plotter, receiving operating characteristic curves, nomogram, and calibration curve. The results were validated using external datasets. Additionally, the correlation of the signature with the immune landscape and drug sensitivity was examined. Furthermore, the effect of LPCAT1 knockdown on HCC cell behavior was verified using in vitro experiments.

Results

This study developed a PANRS. The risk score obtained by using the PANRS was an independent risk factor for the prognosis of patients with HCC and exhibited good prognostic predictive performance. The nomogram constructed based on the risk score and clinical information can accurately predicted the survival probability of patients with HCC. Patients with HCC in the high-risk groups have high immune scores and tend to generate an immunosuppressive microenvironment. They also exhibited a favorable response to immunotherapy, as evidenced by high tumor mutational burden, high immune checkpoint gene expression, high human leukocyte antigen gene expression, low tumor immune dysfunction and low exclusion scores. Additionally, the PANRS enabled the identification of 15 chemotherapeutic agents, including sorafenib, for patients with HCC with different risk levels, guiding clinical treatment. The signature gene LPCAT1 was upregulated in HCC cell lines. LPCAT1 knockdown markedly decreased HCC cell proliferation and migration.

Conclusion

PANRS can accurately predict the prognosis and immunotherapy response of patients with HCC and consequently guide individualized treatment.

SWI/SNF Complex Genomic Alterations as a Predictive Biomarker for Response to Immune Checkpoint Inhibitors in Multiple Cancers

Whether there is an association between SWI/SNF genomic alterations in tumors and response to immune checkpoint inhibitors (ICI) remains unclear because prior studies have focused on either an individual gene or a predefined set of genes. Herein, using mutational and clinical data from 832 ICI-treated patients who underwent whole-exome sequencing, including sequencing of all 31 genes of the SWI/SNF complex, we found that SWI/SNF complex alterations were associated with significantly improved overall survival (OS) in melanoma, clear-cell renal cell carcinoma, and gastrointestinal cancer, as well as improved progression-free survival (PFS) in non-small cell lung cancer. Including tumor mutational burden as a variable, the multivariate Cox regression analysis showed SWI/SNF genomic alterations had prognostic value in melanoma [HR, 0.63 (95% confidence interval, CI, 0.47-0.85), P = 0.003], clear-cell renal cell carcinoma [HR, 0.62 (95% CI, 0.46-0.85), P = 0.003], and gastrointestinal cancer [HR, 0.42 (95% CI, 0.18-1.01), P = 0.053]. Furthermore, we used the random forest method for variable screening, identifying 14 genes as a SWI/SNF signature for potential clinical application. Significant correlations were observed between SWI/SNF signature alterations and improved OS and PFS in all cohorts. This suggests that SWI/SNF gene alterations are associated with better clinical outcomes in ICI-treated patients and may serve as a predictive marker for ICI therapy in multiple cancers.

ATM Inhibition-Induced ISG15/IFI27/OASL Is Correlated with Immunotherapy Response and Inflamed Immunophenotype

Immune checkpoint blockade (ICB) therapy can improve the survival of cancer patients with a high tumor mutation burden (TMB-H) or deficiency in DNA mismatch repair (dMMR) in their tumors. However, most cancer patients without TMB-H and dMMR do not benefit from ICB therapy. The inhibition of ATM can increase DNA damage and activate the interferon response, thus modulating the tumor immune microenvironment (TIME) and the efficacy of ICB therapy. In this study, we showed that ATM inhibition activated interferon signaling and induced interferon-stimulated genes (ISGs) in cisplatin-resistant and parent cancer cells. The ISGs induced by ATM inhibition were correlated with survival in cancer patients who received ICB therapy. In oral cancer, high expressions of ISG15, IFI27, and OASL were associated with low expressions of ATM, the activation of inflamed immune pathways, and increased tumor-infiltrating scores of CD8+ T, natural killer, and dendritic cells. The high expressions of ISG15, IFI27, and OASL were also correlated with complete remission in patients with cervical cancer treated with cisplatin. These results suggest that ATM inhibition can induce the interferon response and inflamed TIME, which may benefit ICB therapy.

Use of the prognostic nutrition index as a predictive biomarker in small-cell lung cancer patients undergoing immune checkpoint inhibitor treatment in the Chinese alpine region

Background

Whether the prognostic nutritional index (PNI), which is suggested to reflect systemic inflammation and nutritional status of patients, could be used as an effective prognostic factor for small-cell lung cancer (SCLC) has not yet been clarified. The purpose of this study was to verify the prognostic value of the PNI in SCLC patients treated with programmed cell death ligand-1/programmed cell death 1 (PD-L1/PD-1) inhibitors in the alpine region of China.

Methods

SCLC patients treated with PD-L1/PD-1 inhibitors monotherapy or combined with chemotherapy between March 2017 and May 2020 were included. Based on the values of serum albumin and total lymphocyte count, the study population was divided into two groups: high and low PNI. The Kaplan-Meier method was used to compute the median survival time and the log-rank test was used to compare the two groups. To evaluate the prognostic value of the PNI, univariable and multivariable analyses of progression-free survival (PFS) and overall survival (OS) were performed. The correlations between PNI and DCR or ORR were calculated by Point biserial correlation analysis.

Results

One hundred and forty patients were included in this study, of which, 60.0% were high PNI (PNI &gt; 49.43) and 40.0% were low PNI (PNI ≤ 49.43). Results indicated that the high PNI group had better PFS and OS than the low PNI group in the patients who received PD-L1/PD-1 inhibitors monotherapy (median PFS: 11.0 vs. 4.8 months, p &lt; 0.001 and median OS: 18.5 vs. 11.0 months, p = 0.004). Similarly, better PFS and OS were associated with an increase in PNI level in the patients who accepted PD-L1/PD-1 inhibitors combined with chemotherapy (median PFS: 11.0 vs. 5.3 months, p &lt; 0.001 and median OS: 17.9 vs. 12.6 months, p = 0.005). Multivariate Cox-regression model showed that high PNI was significantly related to better PFS and OS in patients who accepted PD-L1/PD-1 inhibitors monotherapy or combined with chemotherapy (PD-L1/PD-1 inhibitors monotherapy: PFS: HR = 0.23, 95% CI: 0.10–0.52, p &lt; 0.001 and OS: HR = 0.13, 95% CI: 0.03–0.55, p = 0.006; PD-L1/PD-1 inhibitors combined with chemotherapy: PFS: HR = 0.34, 95% CI: 0.19–0.61, p &lt; 0.001 and OS: HR = 0.53, 95% CI: 0.29–0.97, p = 0.040, respectively). Additionally, Point biserial correlation analysis between PNI and disease control rate (DCR) showed that PNI status was positively correlated with DCR in SCLC patients receiving PD-L1/PD-1 inhibitors or combined with chemotherapy (r = 0.351, p &lt; 0.001; r = 0.285, p &lt; 0.001, respectively).

Concussions

PNI may be a promising biomarker of treatment efficacy and prognosis in SCLC patients treated with PD-L1/PD-1 inhibitors in the alpine region of China.

Evaluating Multiple Next-Generation Sequencing-Derived Tumor Features to Accurately Predict DNA Mismatch Repair Status

Identifying tumor DNA mismatch repair deficiency (dMMR) is important for precision medicine. Tumor features, individually and in combination, derived from whole-exome sequenced (WES) colorectal cancers (CRCs) and panel-sequenced CRCs, endometrial cancers (ECs), and sebaceous skin tumors (SSTs) were assessed for their accuracy in detecting dMMR. CRCs (n = 300) with WES, where mismatch repair status was determined by immunohistochemistry, were assessed for microsatellite instability (MSMuTect, MANTIS, MSIseq, and MSISensor), Catalogue of Somatic Mutations in Cancer tumor mutational signatures, and somatic mutation counts. A 10-fold cross-validation approach (100 repeats) evaluated the dMMR prediction accuracy for i) individual features, ii) Lasso statistical model, and iii) an additive feature combination approach. Panel-sequenced tumors (29 CRCs, 22 ECs, and 20 SSTs) were assessed for the top performing dMMR predicting features/models using these three approaches. For WES CRCs, 10 features provided >80% dMMR prediction accuracy, with MSMuTect, MSIseq, and MANTIS achieving ≥99% accuracy. The Lasso model achieved 98.3% accuracy. The additive feature approach, with three or more of six of MSMuTect, MANTIS, MSIseq, MSISensor, insertion-deletion count, or tumor mutational signature small insertion/deletion 2 + small insertion/deletion 7 achieved 99.7% accuracy. For the panel-sequenced tumors, the additive feature combination approach of three or more of six achieved accuracies of 100%, 95.5%, and 100% for CRCs, ECs, and SSTs, respectively. The microsatellite instability calling tools performed well in WES CRCs; however, an approach combining tumor features may improve dMMR prediction in both WES and panel-sequenced data across tissue types.

Molecular profiling of male breast cancer by multigene panel testing: Implications for precision oncology

Introduction

Compared with breast cancer (BC) in women, BC in men is a rare disease with genetic and molecular peculiarities. Therapeutic approaches for male BC (MBC) are currently extrapolated from the clinical management of female BC, although the disease does not exactly overlap in males and females. Data on specific molecular biomarkers in MBC are lacking, cutting out male patients from more appropriate therapeutic strategies. Growing evidence indicates that Next Generation Sequencing (NGS) multigene panel testing can be used for the detection of predictive molecular biomarkers, including Tumor Mutational Burden (TMB) and Microsatellite Instability (MSI).

Methods

In this study, NGS multigene gene panel sequencing, targeting 1.94 Mb of the genome at 523 cancer-relevant genes (TruSight Oncology 500, Illumina), was used to identify and characterize somatic variants, Copy Number Variations (CNVs), TMB and MSI, in 15 Formalin-Fixed Paraffin-Embedded (FFPE) male breast cancer samples.

Results and discussion

A total of 40 pathogenic variants were detected in 24 genes. All MBC cases harbored at least one pathogenic variant. PIK3CA was the most frequently mutated gene, with six (40.0%) MBCs harboring targetable PIK3CA alterations. CNVs analysis showed copy number gains in 22 genes. No copy number losses were found. Specifically, 13 (86.7%) MBCs showed gene copy number gains. MYC was the most frequently amplified gene with eight (53.3%) MBCs showing a median fold-changes value of 1.9 (range 1.8-3.8). A median TMB value of 4.3 (range 0.8-12.3) mut/Mb was observed, with two (13%) MBCs showing high-TMB. The median percentage of MSI was 2.4% (range 0-17.6%), with two (13%) MBCs showing high-MSI. Overall, these results indicate that NGS multigene panel sequencing can provide a comprehensive molecular tumor profiling in MBC. The identification of targetable molecular alterations in more than 70% of MBCs suggests that the NGS approach may allow for the selection of MBC patients eligible for precision/targeted therapy.

Thiopurine 6TG treatment increases tumor immunogenicity and response to immune checkpoint blockade

Immune-checkpoint inhibitors (ICI) are highly effective in reinvigorating T cells to attack cancer. Nevertheless, a large subset of patients fails to benefit from ICI, partly due to lack of the cancer neoepitopes necessary to trigger an immune response. In this study, we used the thiopurine 6-thioguanine (6TG) to induce random mutations and thus increase the level of neoepitopes presented by tumor cells. Thiopurines are prodrugs which are converted into thioguanine nucleotides that are incorporated into DNA (DNA-TG), where they can induce mutation through single nucleotide mismatching. In a pre-clinical mouse model of a mutation-low melanoma cell line, we demonstrated that 6TG induced clinical-grade DNA-TG integration resulting in an improved tumor control that was strongly T cell dependent. 6TG exposure increased the tumor mutational burden, without affecting tumor cell proliferation and cell death. Moreover, 6TG treatment re-shaped the tumor microenvironment by increasing T and NK immune cells, making the tumors more responsive to immune-checkpoint blockade. We further validated that 6TG exposure improved tumor control in additional mouse models of melanoma. These findings have paved the way for a phase I/II clinical trial that explores whether treatment with thiopurines can increase the proportion of otherwise treatment-resistant cancer patients who may benefit from ICI therapy (NCT05276284).

The Role of Cell-Free DNA in Cancer Treatment Decision Making

The aim of this review is to evaluate the present status of the use of cell-free DNA and its fraction of circulating tumor DNA (ctDNA) because this year July 2022, an ESMO guideline was published regarding the application of ctDNA in patient care. This review is for clinical oncologists to explain the concept, the terms used, the pros and cons of ctDNA; thus, the technical aspects of the different platforms are not reviewed in detail, but we try to help in navigating the current knowledge in liquid biopsy. Since the validated and adequately sensitive ctDNA assays have utility in identifying actionable mutations to direct targeted therapy, ctDNA may be used for this soon in routine clinical practice and in other different areas as well. The cfDNA fragments can be obtained by liquid biopsy and can be used for diagnosis, prognosis, and selecting among treatment options in cancer patients. A great proportion of cfDNA comes from normal cells of the body or from food uptake. Only a small part (<1%) of it is related to tumors, originating from primary tumors, metastatic sites, or circulating tumor cells (CTCs). Soon the data obtained from ctDNA may routinely be used for finding minimal residual disease, detecting relapse, and determining the sites of metastases. It might also be used for deciding appropriate therapy, and/or emerging resistance to the therapy and the data analysis of ctDNA may be combined with imaging or other markers. However, to achieve this goal, further clinical validations are inevitable. As a result, clinicians should be aware of the limitations of the assays. Of course, several open questions are still under research and because of it cfDNA and ctDNA testing are not part of routine care yet.

Cuproptosis-Related LncRNA Signature for Predicting Prognosis of Hepatocellular Carcinoma: A Comprehensive Analysis

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide and has a poor prognosis. Cuproptosis is a novel mode of cell death that has only recently been discovered. Considering the critical role of lncRNAs in liver cancer development, the aim of this study was to construct a prognostic signature based on cuproptosis-related lncRNAs (CRlncRNAs). We downloaded RNA-sequencing data and corresponding clinical information of patients with HCC from The Cancer Genome Atlas (TCGA) database. To verify the robustness of the model, we added an external validation set obtained from the Gene Expression Omnibus (GEO): GSE40144. In addition, we identified the cuproptosis-related genes (CRGs) based on previous reports. Pearson correlation analysis, univariate Cox regression, and least absolute shrinkage and selection operator (LASSO) Cox regression analysis were utilized to screen for genes associated with prognosis. On this basis, multivariate Cox regression and stepAIC were used to further construct and optimize the prognostic model. The simplified signature with the lowest Akaike information criterion (AIC) value was considered the prognostic signature. Seven different algorithms were used to perform immune infiltration analysis. The single-sample Gene Set Enrichment Analysis (ssGSEA) algorithm was utilized to find the difference in immune function between the high- and low-risk groups. Finally, in vitro experiments were performed by quantitative real-time PCR (qRT-PCR) analysis using HCC cell lines to validate the expression of prognostic genes. We identified 3 lncRNAs (CYTOR, LINC00205, and LINC01184) as independent risk factors for HCC. The receiver operating characteristic (ROC) curves calculated that the AUC at 1, 3, and 5 years reached 0.717, 0.633, and 0.607, respectively. The expression levels of 41 immune checkpoints differed significantly between the high- and low-risk groups, and there were significant differences in sensitivity to immunotherapy between the high- and low-risk groups. The risk model could also serve as a promising predictor of immunotherapeutic response, which has been verified by the TIDE algorithm (p < 0.001). Overall, we propose a signature related to CRlncRNAs that can be used to predict the prognosis of HCC patients, which was validated in external cohort and in vitro experiments.

Construction of a B cell-related gene pairs signature for predicting prognosis and immunotherapeutic response in non-small cell lung cancer

BACKGROUND

Accumulating evidence indicates that the B cells play important roles in anti-tumor immunity and shaping tumor development. This study aimed to explore the expression profiles of B cell marker genes and construct a B cell-related gene pairs (BRGPs) signature associated with the prognosis and immunotherapeutic efficiency in non-small cell lung cancer (NSCLC) patients.

METHODS

B cell-related marker genes in NSCLC were identified using single-cell RNA sequencing data. TCGA and GEO datasets were utilized to identify the prognostic BRGPs based on a novel algorithm of cyclically single pairing along with a 0-or-1 matrix. BRGPs signature was then constructed using Lasso-Cox regression model. Its prognostic value, associated immunogenomic features, putative molecular mechanism and predictive ability to immunotherapy were investigated in NSCLC patients.

RESULTS

The BRGPs signature was composed of 23 BRGPs including 28 distinct B cell-related genes. This predictive signature demonstrated remarkable power in distinguishing good or poor prognosis and can serve as an independent prognostic factor for NSCLC patients in both training and validation cohorts. Furthermore, BRGPs signature was significantly associated with immune scores, tumor purity, clinicopathological characteristics and various tumor-infiltrating immune cells. Besides, we demonstrated that the tumor mutational burden scores and TIDE scores were positively correlated with the risk score of the model implying immune checkpoint blockade therapy may be more effective in NSCLC patients with high-risk scores.

CONCLUSIONS

This novel BRGPs signature can be used to assess the prognosis of NSCLC patients and may be useful in guiding immune checkpoint inhibitor treatment in our clinical practice.

Targeting myeloid villains in the treatment with immune checkpoint inhibitors in gastrointestinal cancer

Despite the clinical outcomes being extremely limited, blocking immune inhibitory checkpoint pathways has been in the spotlight as a promising strategy for treating gastrointestinal cancer. However, a distinct strategy for the successful treatment is obviously needed in the clinical settings. Myeloid cells, such as neutrophils, macrophages, dendritic cells, and mast cells, are the majority of cellular components in the human immune system, but have received relatively less attention for the practical implementation than T cells and NK cells in cancer therapy because of concentration of the interest in development of the immune checkpoint blocking antibody inhibitors (ICIs). Abnormality of myeloid cells must impact on the entire host, including immune responses, stromagenesis, and cancer cells, leading to refractory cancer. This implies that elimination and reprogramming of the tumor-supportive myeloid villains may be a breakthrough to efficiently induce potent anti-tumor immunity in cancer patients. In this review, we provide an overview of current situation of the IC-blocking therapy of gastrointestinal cancer, including gastric, colorectal, and esophageal cancers. Also, we highlight the possible oncoimmunological components involved in the mechanisms underlying the resistance to the ICI therapy, particularly focusing on myeloid cells, including unique subsets expressing IC molecules. A deeper understanding of the molecular and cellular determinants may facilitate its practical implementation of targeting myeloid villains, and improve the clinical outcomes in the ICI therapy of gastrointestinal cancer.

Systematic review of the CUP trials characteristics and perspectives for next-generation studies

BACKGROUND

Research on therapeutic strategies for patients with unknown primary cancer (CUP) has been underwhelming. This paper summarized and evaluated the CUP therapeutic research over the previous five years. Based on this evaluation, recommendations for clinical trial designs are made to improve the impact of CUP research on patients.

METHODS

Published and ongoing research were evaluated. PubMed was searched from January 1, 2015, to November 1, 2021. The start date of 2015 was chosen to identify research published after ESMO issued new diagnostic and therapeutic guidelines. The US National Library of Medicine indexed ongoing clinical trials.

FINDINGS

Of the 244 CUP studies indexed in PubMed, 11.9% were prospective studies, and 4.9% were clinical trials. The review protocol deemed 65 publications eligible for full-text review. Eleven studies evaluating therapeutic regimens were retained. The two prospective studies and non-randomized trials showed promising outcomes for site-specific treatments. Randomized clinical trials were less promising; however, the trials had recruitment challenges resulting in biased accrual and the inability to keep pace with advancing diagnostics and therapeutics. Most of the 35 ongoing studies were phase II single-arm trials assessing immune checkpoint inhibitors (ICI) or site-specific therapies among CUP patients with suspected favorable prognoses.

CONCLUSION

Our evaluation suggests two prospective clinical trial designs that addressed recent study design and recruitment challenges. A visionary approach uses a multi-arm, multistage randomized trial to address rapid advancements in diagnosis and therapy. A pragmatic approach utilizes a single-arm trial with historical controls to overcome comparison group and recruitment challenges.