Tumor Mutational Burden as a Predictive Biomarker in Solid Tumors

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.

Integrating knowledge graphs into machine learning models for survival prediction and biomarker discovery in patients with non-small-cell lung cancer

Accurate survival prediction for Non-Small Cell Lung Cancer (NSCLC) patients remains a significant challenge for the scientific and clinical community despite decades of advanced analytics. Addressing this challenge not only helps inform the critical aspects of clinical study design and biomarker discovery but also ensures that the 'right patient' receives the 'right treatment'. However, survival prediction is a highly complex task, given the large number of 'omics; and clinical features, as well as the high degree of freedom that drive patient survival. Prior knowledge could play a critical role in uncovering the complexity of a disease and understanding the driving factors affecting a patient's survival. We introduce a methodology for incorporating prior knowledge into machine learning-based models for prediction of patient survival through Knowledge Graphs, demonstrating the advantage of such an approach for NSCLC patients. Using data from patients treated with immuno-oncologic therapies in the POPLAR (NCT01903993) and OAK (NCT02008227) clinical trials, we found that the use of knowledge graphs yielded significantly improved hazard ratios, including in the POPLAR cohort, for models based on biomarker tumor mutation burden compared with those based on knowledge graphs. Use of a model-defined mutational 10-gene signature led to significant overall survival differentiation for both trials. We provide parameterized code for incorporating knowledge graphs into survival analyses for use by the wider scientific community.

Entering the TiME machine: How age-related changes in the tumor immune microenvironment impact melanoma progression and therapy response

Melanoma is the deadliest form of skin cancer in the United States, with its incidence rates rising in older populations. As the immune system undergoes age-related changes, these alterations can significantly influence tumor progression and the effectiveness of cancer treatments. Recent advancements in understanding immune checkpoint molecules have paved the way for the development of innovative immunotherapies targeting solid tumors. However, the aging tumor microenvironment can play a crucial role in modulating the response to these immunotherapeutic approaches. This review seeks to examine the intricate relationship between age-related changes in the immune system and their impact on the efficacy of immunotherapies, particularly in the context of melanoma. By exploring this complex interplay, we hope to elucidate potential strategies to optimize treatment outcomes for older patients with melanoma, and draw parallels to other cancers.

Immune-based Therapies for Penile Cancer

This article reviews penile squamous cell carcinoma (PSCC), a rare genitourinary cancer that has been increasing in prevalence. It discusses emerging therapies, focusing on immunotherapy, vaccine therapy, and cell-based treatments, especially in the context of human papillomavirus-related PSCC. Factors influencing these therapies are discussed. These include the immune microenvironment, programmed cell death ligand-1 expression, and tumor immune cell infiltration. This article also highlights immune checkpoint inhibitors and related clinical trials. This review supports the use of personalized medicine in treating PSCC. It stresses the need for collaborative studies and data sharing to create specific treatment plans and achieve better outcomes.

A pan-cancer analysis of the core pre-mRNA 3' end processing factors, and their association with prognosis, tumor microenvironment, and potential targets

Alternative polyadenylation (APA) is a crucial mechanism for regulating gene expression during pre-mRNA 3' processing. Pre-mRNA 3' end processing factors is the main factor involved in this process. However, pre-mRNA 3' end processing factors in different cancer expression profiles and the relationship between pre-mRNA 3' end processing factors and tumor microenvironment and the prognosis of the same patient is still unclear. In this study, we conducted a comprehensive exploration of the core pre-mRNA 3' end processing factors across various cancer types by utilizing common cancer database, and revealing a robust correlation between the expression of these core factors and tumor characteristics. Leveraging advanced bioinformatics databases, we evaluated the expression levels and prognostic relevance of pre-mRNA 3' end processing factors across pan-cancer tissues. Our extensive pan-cancer analysis revealed unique expression patterns of pre-mRNA 3' end processing factors in both tumor and adjacent non-tumorous tissues. Notably, we found a significant correlation between the expression levels of pre-mRNA 3' end processing factors and patient prognosis. Furthermore, we identified strong associations between pre-mRNA 3' end processing factors expression and various factors, such as stromal, immune, RNA stemness, and DNA stemness scores across pan-cancer tissues. Our data also highlighted a link between the expression of pre-mRNA 3' end processing factors and sensitivity to specific drugs, including pyrazoloacndine, amonaflide, and chelerythrinede, among others. We found four key pre-mRNA 3' end processing factors that play a crucial role in mRNA preprocessing. Our study illuminates the potential promotion and inhibition role of pre-mRNA 3' end processing regulators in the progression of cancer, CPSF2, CPSF3, CSTF2, SYMPK offering valuable insights for future research investigations on these regulators as diagnostic markers and therapeutic targets across pan-cancer.

Identification of N6-Methyladenosine-Associated lncRNAs and Analysis of Prognostic Signature in Breast Cancer

Breast cancer represents the predominant malignant neoplasm in women, posing significant threats to both life and health. N6-methyladenosine (m6A) methylation, the most prevalent RNA modification, plays a crucial role in cancer development. This study aims to delineate the prognostic implications of m6A-associated long non-coding RNAs (m6AlncRNAs) and identify potential m6AlncRNA candidates as novel therapeutic targets for breast cancer. Through univariate Cox, Least Absolute Shrinkage and Selection Operator and multiple Cox regression analysis, m6AlncRNA was analyzed and a risk-prognosis model was constructed. Kaplan-Meier analysis, principal component analysis and nomogram were used to evaluate the risk model. Finally, we screened candidate lncRNAs and validated them in breast cancer cell lines. m6AlncRNAs were stratified into three subtypes, and their associations with survival outcomes and immune infiltrating capacities were systematically analyzed. Subsequently, breast cancer patients were stratified into high and low-risk groups based on median risk scores, revealing distinct clinical characteristics, tumor immunoinvasive profiles, tumor mutation burden, and survival probabilities. Additionally, a prognostic model was established, highlighting three promising candidate lncRNAs: ECE1-AS1, NDUFA6-DT, and COL4A2-AS1. This study investigated the prognostic implications of m6A-associated long non-coding RNAs (m6AlncRNAs) and developed a prognostic risk model to identify three potential m6AlncRNA candidates. These findings provide valuable insights into the potential application of these m6AlncRNAs in guiding immunotherapeutic strategies for breast cancer.

Biomarker development for PD-(L)1 axis inhibition: a consensus view from the SITC Biomarkers Committee

Therapies targeting the programmed cell death protein-1/programmed death-ligand 1 (PD-L1) (abbreviated as PD-(L)1) axis are a significant advancement in the treatment of many tumor types. However, many patients receiving these agents fail to respond or have an initial response followed by cancer progression. For these patients, while subsequent immunotherapies that either target a different axis of immune biology or non-immune combination therapies are reasonable treatment options, the lack of predictive biomarkers to follow-on agents is impeding progress in the field. This review summarizes the current knowledge of mechanisms driving resistance to PD-(L)1 therapies, the state of biomarker development along this axis, and inherent challenges in future biomarker development for these immunotherapies. Innovation in the development and application of novel biomarkers and patient selection strategies for PD-(L)1 agents is required to accelerate the delivery of effective treatments to the patients most likely to respond.

Genetic and epigenetic instability as an underlying driver of progression and aggressive behavior in IDH-mutant astrocytoma

In recent years, the classification of adult-type diffuse gliomas has undergone a revolution, wherein specific molecular features now represent defining diagnostic criteria of IDH-wild-type glioblastomas, IDH-mutant astrocytomas, and IDH-mutant 1p/19q-codeleted oligodendrogliomas. With the introduction of the 2021 WHO CNS classification, additional molecular alterations are now integrated into the grading of these tumors, given equal weight to traditional histologic features. However, there remains a great deal of heterogeneity in patient outcome even within these established tumor subclassifications that is unexplained by currently codified molecular alterations, particularly in the IDH-mutant astrocytoma category. There is also significant intercellular genetic and epigenetic heterogeneity and plasticity with resulting phenotypic heterogeneity, making these tumors remarkably adaptable and robust, and presenting a significant barrier to the design of effective therapeutics. Herein, we review the mechanisms and consequences of genetic and epigenetic instability, including chromosomal instability (CIN), microsatellite instability (MSI)/mismatch repair (MMR) deficits, and epigenetic instability, in the underlying biology, tumorigenesis, and progression of IDH-mutant astrocytomas. We also discuss the contribution of recent high-resolution transcriptomics studies toward defining tumor heterogeneity with single-cell resolution. While intratumoral heterogeneity is a well-known feature of diffuse gliomas, the contribution of these various processes has only recently been considered as a potential driver of tumor aggressiveness. CIN has an independent, adverse effect on patient survival, similar to the effect of histologic grade and homozygous CDKN2A deletion, while MMR mutation is only associated with poor overall survival in univariate analysis but is highly correlated with higher histologic/molecular grade and other aggressive features. These forms of genomic instability, which may significantly affect the natural progression of these tumors, response to therapy, and ultimately clinical outcome for patients, are potentially measurable features which could aid in diagnosis, grading, prognosis, and development of personalized therapeutics.

Identification of a novel apoptosis-related genes signature to improve gastric cancer prognosis prediction

Dysregulation of apoptosis occurs in different types of malignant tumors and is likely to influence the tumor evolution, as well as clinical prognosis. However, the limited number of studies investigating the predictive power of apoptosis-related genes (ARGs) in gastric cancer indicates a gap in the current research. 174 ARGs who differentially expressed were screened using public databases, including the Gene Expression Omnibus and the Molecular Signatures Database. Univariate and LASSO regression analyses were rigorous approaches to recognize the 12 optimal genes (CTHRC1, PDGFRL, VCAN, GJA1, LOX, UPP1, ANGPT2, CRIM1, HIF1A, APOD, RNase1, and ID1) that make up the prognostic risk model. Molecular mutations, related signaling pathways, and immune system characteristics in different subgroups defined by the risk model were analyzed using different R packages. Moreover, based on the database of Genomics of Drug Sensitivity in Cancer, chemotherapy sensitivity was predicted among the risk subgroups. As a result, there were differences in mutation profiles, signaling pathways, and infiltrated immune cells between patients in various risk groups. Moreover, the low-risk group displayed greater sensitivity to chemotherapy than the high-risk group. Risk model provided a better prognostic value than the T, N, and M stages, according to the receiver operating characteristic curve. Finally, in a nomogram, the risk model and clinical factors were combined to visualize the survival rates of patients with GC. In response to the differential expression of apoptosis-related genes, a novel model for predicting the prognosis of GC patients was developed. This model may be highly valuable for guiding doctors to deliver treatment plans tailored to the need of patients with GC.

Tissue-specific thresholds of mutation burden associated with anti-PD-1/L1 therapy benefit and prognosis in microsatellite-stable cancers

Immune checkpoint inhibitors (ICIs) targeting programmed cell death protein 1 or its ligand (PD-1/L1) have expanded the treatment landscape against cancers but are effective in only a subset of patients. Tumor mutation burden (TMB) is postulated to be a generic determinant of ICI-dependent tumor rejection. Here we describe the association between TMB and survival outcomes among microsatellite-stable cancers in a real-world clinicogenomic cohort consisting of 70,698 patients distributed across 27 histologies. TMB was associated with survival benefit or detriment depending on tissue and treatment context, with eight cancer types demonstrating a specific association between TMB and improved outcomes upon treatment with anti-PD-1/L1 therapies. Survival benefits were noted over a broad range of TMB cutoffs across cancer types, and a dose-dependent relationship between TMB and outcomes was observed in a subset of cancers. These results have implications for the use of cancer-agnostic and universal TMB cutoffs to guide the use of anti-PD-1/L1 therapies, and they underline the importance of tissue context in the development of ICI biomarkers.

Clinical Practice Recommendations for the Use of Next-Generation Sequencing in Patients with Solid Cancer: A Joint Report from KSMO and KSP

In recent years, next-generation sequencing (NGS)-based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

Clinical practice recommendations for the use of next-generation sequencing in patients with solid cancer: a joint report from KSMO and KSP

In recent years, next-generation sequencing (NGS)-based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

Pan-Cancer Analysis Links Altered RNA m7G Methyltransferase Expression to Oncogenic Pathways, Immune Cell Infiltrations and Overall Survival

BACKGROUND

N7-methylguanosine (m7G) modification is one of the most prevalent RNA modifications in humans. Dysregulated m7G modifications caused by aberrant expression of m7G writers contribute to cancer progression and result in worse patient survival in several human cancers. However, studies that systematically assess the frequency and clinical relevance of aberrant m7G writer expression in a pan-cancer cohort remain to be performed.

AIMS

This study aims to systematically investigate the molecular alteration and clinical relevance of m7G methyltransferase in human cancers.

METHODS

We analysed genome, transcriptome and clinical data from the Cancer Genome Atlas Research Network spanning 33 types of human cancers for aberrant changes in genes encoding m7G writers.

RESULT

We demonstrate that m7G writers are dysregulated in human cancers and are associated predominantly with poorer survival. By dividing patients into those with high and low m7G scores, we show that a lower m7G score is generally associated with immune infiltration and better response to immunotherapy.

CONCLUSION

Our analyses indicate the genetic alterations, expression patterns and clinical relevance of m7G writers across various cancers. This study provides insights into the potential utility of m7G writer expression as a cancer biomarker and proposes the possibility of targeting m7G writers for cancer therapy.

Intrapatient variation in PD-L1 expression and tumor mutational burden and the impact on outcomes to immune checkpoint inhibitor therapy in patients with non-small cell lung cancer

BACKGROUND

PD-L1 tumor proportion score (TPS) and tumor mutational burden (TMB) are key predictive biomarkers for immune checkpoint inhibitors (ICI) efficacy in non-small cell lung cancer (NSCLC). Data on their variation across multiple samples are limited.

METHODS

Patients with NSCLC and multiple PD-L1 TPS and/or TMB assessments were included. Clinicopathologic and genomic data were analyzed according to PD-L1 and TMB variation.

RESULTS

In total, 402 PD-L1 sample pairs and 413 TMB sample pairs were included. Concordance between pairs was moderate for PD-L1 (ρ=0.53, P<0.0001) and high for TMB (ρ=0.80, P<0.0001). Shorter time between biopsies correlated with higher concordance in PD-L1, but not in TMB. Major increases (ΔTPS≥+50%) and decreases (ΔTPS≤-50%) in PD-L1 were observed in 9.7% and 8.0% of cases, respectively. PD-L1, but not TMB, decreased with intervening ICI (P=0.02). Acquired copy number loss of CD274, PDCD1LG2, and JAK2 were associated with major decrease in PD-L1 (q<0.05). Among patients with multiple PD-L1 assessments before ICI, cases where all samples had a PD-L1 ≥1%, compared to cases with at least one sample with PD-L1 <1% and another with PD-L1 ≥1%, achieved improved objective response rate and progression-free survival (PFS). Among patients with at least one PD-L1 <1% and one ≥1% before ICI, cases where the most proximal sample was PD-L1 ≥1% had longer median PFS compared to cases where the most proximal PD-L1 was <1%. Among patients with multiple TMB assessments before ICI, patients with a TMB ≥10 mut/Mb based on the most recent assessment, as compared to those with a TMB <10 mut/Mb, achieved improved PFS and OS to ICI; instead, no differences were observed when patients were categorized using the oldest TMB assessment.

CONCLUSION

Despite intrapatient concordance in PD-L1 and TMB, variation in these biomarkers can influence ICI outcomes, warranting consideration for reassessment prior to ICI initiation when feasible.

Immunotherapy in melanoma: advances, pitfalls, and future perspectives

Cutaneous melanoma is the deadliest and most aggressive form of skin cancer owing to its high capacity for metastasis. Over the past few decades, the management of this type of malignancy has undergone a significant revolution with the advent of both targeted therapies and immunotherapy, which have greatly improved patient quality of life and survival. Nevertheless, the response rates are still unsatisfactory for the presence of side effects and development of resistance mechanisms. In this context, tumor microenvironment has emerged as a factor affecting the responsiveness and efficacy of immunotherapy, and the study of its interplay with the immune system has offered new promising clinical strategies. This review provides a brief overview of the currently available immunotherapeutic strategies for melanoma treatment by analyzing both the positive aspects and those that require further improvement. Indeed, a better understanding of the mechanisms involved in the immune evasion of melanoma cells, with particular attention on the role of the tumor microenvironment, could provide the basis for improving current therapies and identifying new predictive biomarkers.

Medullary Thyroid Cancer: Molecular Drivers and Immune Cellular Milieu of the Tumour Microenvironment-Implications for Systemic Treatment

In this review, we explore the underlying molecular biology of medullary thyroid carcinoma (MTC) and its interplay with the host immune system. MTC is consistently driven by a small number of specific pathogenic variants, beyond which few additional genetic events are required for tumorigenesis. This explains the exceedingly low tumour mutational burden seen in most MTC, in contrast to other cancers. However, because of the low tumour mutational burden (TMB), there is a correspondingly low level of tumour-associated neoantigens that are presented to the host immune system. This reduces tumour visibility and vigour of the anti-tumour immune response and suggests the efficacy of immunotherapy in MTC is likely to be poor, acknowledging this inference is largely based on the extrapolation of data from other tumour types. The dominance of specific RET (REarranged during Transfection) pathogenic variants in MTC tumorigenesis rationalizes the observed efficacy of the targeted RET-specific tyrosine kinase inhibitors (TKIs) in comparison to multi-kinase inhibitors (MKIs). Therapeutic durability of pathway inhibitors is an ongoing research focus. It may be limited by the selection pressure TKI treatment creates, promoting survival of resistant tumour cell clones that can escape pathway inhibition through binding-site mutations, activation of alternate pathways, and modulation of the cellular and cytokine milieu of the tumour microenvironment (TME).

Previous radiotherapy increases the efficacy of cemiplimab in the treatment of locally advanced and metastatic cutaneous squamous cell carcinoma: A retrospective analysis

BACKGROUND

Cemiplimab, a programmed cell death-1 inhibitor approved in 2018 for patients with locally advanced or metastatic cutaneous squamous cell carcinoma (cSCC) who are ineligible for curative therapies, lacks clarity regarding the optimal patient selection despite its known efficacy.

OBJECTIVE

This retrospective study aims to assess the real-world treatment patterns and outcomes in patients with cSCC at our institution.

METHODS

A retrospective analysis of consecutively treated patients with cemiplimab for cSCC was conducted. Progression-free survival (PFS) and overall survival were evaluated alongside clinical-pathologic characteristics.

RESULTS

Forty-five patients were included, of which 73.3% were male with a median age of 77 years. After 18 months of median follow-up median PFS and overall survival were not reached with a mean of 21.3 months ± 2.2 months and 25.3 ± 2.1 months, respectively. Univariate and multivariate analyses revealed significant correlations only between PFS and previous radiotherapy (P values: .043 and .046, respectively).

LIMITATIONS

Limitations include its retrospective nature, the low number of patients analyzed, and the potential for inherent biases.

CONCLUSIONS

The study reveals a significant association between prior radiotherapy and improved PFS in cemiplimab-treated cSCC, suggesting the potential for combining radiotherapy with cemiplimab. Further exploration of this combined approach is warranted.

Biomarker-triggered, spatiotemporal controlled DNA nanodevice simultaneous assembly and disassembly

Despite many advances in the use of DNA nanodevices as assembly or disassembly modules to build various complex structures, the simultaneous assembly and disassembly of DNA structures in living cells remains a challenge. In this study, we present a modular engineering approach for assembling and disassembling DNA nanodevices in response to endogenous biomarkers. As a result of pairwise prehybridization of original DNA strands, the DNA nanodevice is initially inert. In an effort to bind one of the paired strands and release its complement, nucleolin competes. Assembly of the DNA nanodevice is initiated when the released complement binds to it, and disassembly is initiated when APE1 shears the assembled binding site of the DNA nanodevice. Spatial-temporal logic control is achieved through our approach during the assembly and disassembly of DNA nanodevices. Furthermore, by means of this assembly and disassembly procedure, the sequential detection and imaging of two tumor markers can be achieved, thereby effectively reducing false-positive signal results and accelerating the detection time. This study emphasizes the simultaneous assembly and disassembly of DNA nanodevices controlled by biomarkers in a simple and versatile manner; it has the potential to expand the application scope of DNA nanotechnology and offers an idea for the implementation of precision medicine testing.

Assessing the predictive value of smoking history for immunotherapy outcomes in bladder cancer patients

Background

The therapeutic effectiveness of immune checkpoint inhibitors (ICIs) in bladder cancer varies among individuals. Identifying reliable predictors of response to these therapies is crucial for optimizing patient outcomes.

Methods

This retrospective study analyzed 348 bladder cancer patients treated with ICIs, with additional validation using data from 248 patients at our institution who underwent PD-L1 immunohistochemical staining. We examined patient smoking history, clinicopathological characteristics, and immune phenotypes. The main focus was the correlation between smoking history and immunotherapy outcomes. Multivariate logistic and Cox proportional hazard regressions were used to adjust for confounders.

Results

The study cohort comprised 348 bladder cancer patients receiving ICIs. Among them, 116 (33.3%) were never smokers, 197 (56.6%) were former smokers (median pack-years = 28), and 35 (10.1%) were current smokers (median pack-years = 40). Analysis revealed no statistically significant difference in overall survival across different smoking statuses (objective response rates were 11.4% for current smokers, 17.2% for never smokers, and 22.3% for former smokers; P = 0.142, 0.410, and 0.281, respectively). However, a notable trend indicated a potentially better response to immunotherapy in former smokers compared to current and never smokers. In the validation cohort of 248 patients from our institution, immunohistochemical analysis showed that PD-L1 expression was significantly higher in former smokers (55%) compared to current smokers (37%) and never smokers (47%). This observation underscores the potential influence of smoking history on the tumor microenvironment and its responsiveness to ICIs.

Conclusion

In conclusion, our study demonstrates the importance of incorporating smoking history in predicting the response to immunotherapy in bladder cancer patients, highlighting its role in personalized cancer treatment approaches. Further research is suggested to explore the comprehensive impact of lifestyle factors on treatment outcomes.

Immunotherapy: The Fourth Domain in Oral Cancer Therapeutics

Owing to high global prevalence, incidence and associated mortality, cancer of head and neck particularly oral cancer remains a cardinal domain for research and trials. Immune-modulatory therapies that employ patients own immune system for therapeutic benefits in oral cancer seems promising. The aim of this review is to gauge the potential of immunotherapy as fourth domain of Oral cancer therapeutics. Articles were searched using suitable search terms in MEDLINE and Google Scholar database to include clinical trials, meta-analyses, and research in humans/animals/cell lines published in peer reviewed journals. A total of 97 articles were included in this review. Literature has several studies and trials where different types of immunotherapies has been attempted but it is crucial to identify precise biomarkers of genome based targeted agents and to find parameters to select patients who might benefit from immunotherapy. Also further research is required to estimate predictive value of tumor mutational burden and mutational signatures so as to aid in personalized prediction of oral cancer therapeutic response.

Metabolic reprogramming-driven homologous recombination and TCA cycle dysregulation contribute to poor prognoses in lung adenocarcinoma

Increasing evidence has shown that homologous recombination (HR) and metabolic reprogramming are essential for cellular homeostasis. These two processes are independent as well as closely intertwined. Nevertheless, they have rarely been reported in lung adenocarcinoma (LUAD). We analysed the genomic, immune microenvironment and metabolic microenvironment features under different HR activity states. Using cell cycle, EDU and cell invasion assays, we determined the impacts of si-SHFM1 on the LUAD cell cycle, proliferation and invasion. The levels of isocitrate dehydrogenase (IDH) and α-ketoglutarate dehydrogenase (α-KGDH) were determined by ELISA in the NC and si-SHFM1 groups of A549 cells. Finally, cell samples were used to extract metabolites for HPIC-MS/MS to analyse central carbon metabolism. We found that high HR activity was associated with a poor prognosis in LUAD, and HR was an independent prognostic factor for TCGA-LUAD patients. Moreover, LUAD samples with a high HR activity presented low immune infiltration levels, a high degree of genomic instability, a good response status to immune checkpoint blockade therapy and a high degree of drug sensitivity. The si-SHFM1 group presented a significantly higher proportion of cells in the G0/G1 phase, lower levels of DNA replication, and significantly lower levels of cell migration and both TCA enzymes. Our current results indicated that there is a strong correlation between HR and the TCA cycle in LUAD. The TCA cycle can promote SHFM1-mediated HR in LUAD, raising their activities, which can finally result in a poor prognosis and impair immunotherapeutic efficacy.

Molecular classification and intratumoral heterogeneity of gastric adenocarcinoma

Gastric cancers frequently harbor striking histological complexity and diversity between lesions as well as within single lesions, known as inter- and intratumoral heterogeneity, respectively. The latest World Health Organization Classification of Tumors designated more than 30 histological subtypes for gastric epithelial tumors, assigning 12 subtypes for gastric adenocarcinoma (GAD). Meanwhile, recent advances in genome-wide analyses have provided molecular aspects to the histological classification of GAD, and consequently revealed different molecular traits underlying these histological subtypes. Moreover, accumulating knowledge of comprehensive molecular profiles has led to establishing molecular classifications of GAD, which are often associated with clinical biomarkers for therapeutics and prognosis. However, most of our knowledge of GAD molecular profiles is based on inter-tumoral heterogeneity, and the molecular profiles underlying intratumoral heterogeneity are yet to be determined. In this review, recently established molecular classifications of GAD are introduced in the aspect of pathological diagnosis and are discussed in the context of intratumoral heterogeneity.

Microsatellite Instability, Mismatch Repair, and Tumor Mutation Burden in Lung Cancer

Since US Food and Drug Administration approval of programmed death ligand 1 (PD-L1) as the first companion diagnostic for immune checkpoint inhibitors (ICIs) in non-small cell lung cancer, many patients have experienced increased overall survival. To improve selection of ICI responders versus nonresponders, microsatellite instability/mismatch repair deficiency (MSI/MMR) and tumor mutation burden (TMB) came into play. Clinical data show PD-L1, MSI/MMR, and TMB are independent predictive immunotherapy biomarkers. Harmonization of testing methodologies, optimization of assay design, and results analysis are ongoing. Future algorithms to determine immunotherapy eligibility might involve complementary use of current and novel biomarkers. Artificial intelligence could facilitate algorithm implementation to convert complex genetic data into recommendations for specific ICIs.

High-throughput molecular assays for inclusion in personalised oncology trials - State-of-the-art and beyond

In the last decades, the development of high-throughput molecular assays has revolutionised cancer diagnostics, paving the way for the concept of personalised cancer medicine. This progress has been driven by the introduction of such technologies through biomarker-driven oncology trials. In this review, strengths and limitations of various state-of-the-art sequencing technologies, including gene panel sequencing (DNA and RNA), whole-exome/whole-genome sequencing and whole-transcriptome sequencing, are explored, focusing on their ability to identify clinically relevant biomarkers with diagnostic, prognostic and/or predictive impact. This includes the need to assess complex biomarkers, for example microsatellite instability, tumour mutation burden and homologous recombination deficiency, to identify patients suitable for specific therapies, including immunotherapy. Furthermore, the crucial role of biomarker analysis and multidisciplinary molecular tumour boards in selecting patients for trial inclusion is discussed in relation to various trial concepts, including drug repurposing. Recognising that today's exploratory techniques will evolve into tomorrow's routine diagnostics and clinical study inclusion assays, the importance of emerging technologies for multimodal diagnostics, such as proteomics and in vivo drug sensitivity testing, is also discussed. In addition, key regulatory aspects and the importance of patient engagement in all phases of a clinical trial are described. Finally, we propose a set of recommendations for consideration when planning a new precision cancer medicine trial.

A cloud-based precision oncology framework for whole genome sequence analysis

Cancer is one of the wide-ranging diseases which have a high mortality rate impacting globally. This scenario can be switched by early detection and correct precision treatment, a major concern for cancer patients. Clinicians can figure out the best-suited treatments for cancer patients by analyzing the patient's genome, which will treat the patient well and minimize the chances of side effects as well. Therefore, we have developed a fast, robust, and efficient solution as our precision oncology framework based on the whole genome sequencing of the individual's DNA. This platform can perform the entire genomic analysis, starting from the quality assessment of the input file to the variant annotation and functional prediction, followed by a certain level of interpretation. This analysis helps in the molecular profiling of the tumors for the identification of the targetable alterations. It takes in FASTQ or BAM file as an input and provides us with two output reports: a primary report, which consists of the patients' details, a summary of the analysis, and a secondary report, which is an elaborated report comprised of numerous results obtained from the analysis such as base changes, codon changes, amino acid changes, TMB analysis, MSI analysis, the variant frequency with its effects and impacts, affected biomarkers, etc. This framework can be effectively utilized for cancer treatment guidance, identification and validation of novel biomarkers, oncology research & development, genomic analysis, and gene manipulation.

The Evolving Landscape of Biomarkers for Immune Checkpoint Blockade in Genitourinary Cancers

In the past decade, immune checkpoint inhibitors (ICI) have been approved for treatment of genitourinary malignancies and have revolutionized the treatment landscape of these tumors. However, despite the remarkable success of these therapies in some GU malignancies, many patients' tumors do not respond to these therapies, and others may experience significant side effects, such as immune-related adverse events (iRAEs). Accordingly, biomarkers and improved prognostic tools are critically needed to help predict which patients will respond to ICI, predict and mitigate risk of developing immune-related adverse events, and inform personalized choice of therapy for each patient. Ongoing clinical and preclinical studies continue to provide an increasingly robust understanding of the mechanisms of the response to immunotherapy, which continue to inform biomarker development and validation. Herein, we provide a comprehensive review of biomarkers of the response to immunotherapy in GU tumors and their role in selection of therapy and disease monitoring.

IL4I1: a novel molecular biomarker represents an inflamed tumor microenvironment and precisely predicts the molecular subtype and immunotherapy response of bladder cancer

Introduction: IL4I1, also known as Interleukin-4-induced gene 1, is an enzyme that can modulate the immune system by acting as a L-amino acid oxidase. Nevertheless, a precise understanding of the correlation of IL4I1 with immunological features and immunotherapy efficacy in bladder cancer (BLCA) remains incomplete. Methods: We analyzed RNA sequencing data from the Cancer Genome Atlas (TCGA) to investigate the immune function and prognostic importance of IL4I1 across different cancer types. We further examined the TCGA-BLCA cohort for correlations between IL4I1 and various immunological characteristics of tumor microenvironment (TME), such as cancer immune cycle, immune cell infiltration, immune checkpoint expression and T cell inflamed score. Validation was conducted using two independent cohort, GSE48075 and E-MTAB-4321. Finally, RNA sequencing data from the IMvigor210 cohort and immunohistochemistry assays were employed to validate the predictive value of IL4I1 for the TME and immunotherapy efficacy. Results: In our findings, a positive correlation was observed between IL4I1 expression and immunomodulators expression, immune cell infiltration, the cancer immune cycle, and T cell inflamed score in BLCA, suggesting a significant link to the inflamed TME. In addition, studies have shown that IL4I1 elevated levels of individuals tend to be more performance for basal subtype and exhibit enhanced response rates to diverse treatment modalities, specifically immunotherapy. Clinical data from the IMvigor 210 cohort confirmed a higher rate of response to immunotherapy and better survival benefits in patients with high IL4I1 expression. Discussion: To summarize, our research showed that elevated IL4I1 levels are indicative of an inflamed TME, the basal subtype, and a more favorable response to various treatment methods, especially immune checkpoint blockade therapy in BLCA.

FAT1 as a tumor mutation burden specific gene affects the immunotherapy effect in head and neck squamous cell cancer

BACKGROUND

Response to immunotherapy is the main challenge of head and neck squamous cancer (HNSCC) treatment. Previous studies have indicated that tumor mutational burden (TMB) is associated with prognosis, but it is not always a precise index. Hence, investigating specific genetic mutations and tumor microenvironment (TME) changes in TMB-high patients is essential for precision therapy of HNSCC.

METHODS

A total of 33 HNSCC patients were enrolled in this study. We calculated the TMB score based on next-generation sequencing (NGS) sequencing and grouped these patients based on TMB score. Then, we examined the immune microenvironment of HNSCC using assessments of the bulk transcriptome and the single-cell RNA sequence (scRNA-seq) focusing on the molecular nature of TMB and mutations in HNSCC from our cohort. The association of the mutation pattern and TMB was analyzed in The Cancer Genome Atlas (TCGA) and validated by our cohort.

RESULTS

33 HNSCC patients were divided into three groups (TMB-low, -medium, and -high) based on TMB score. In the result of 520-gene panel sequencing data, we found that FAT1 and LRP1B mutations were highly prevalent in TMB-high patients. FAT1 mutations are associated with resistance to immunotherapy in HNSCC patients. This involves many metabolism-related pathways like RERE, AIRE, HOMER1, etc. In the scRNA-seq data, regulatory T cells (Tregs), monocytes, and DCs were found mainly enriched in TMB-high samples.

CONCLUSION

Our analysis unraveled the FAT1 gene as an assistant predictor when we use TMB as a biomarker of drug resistance in HNSCC. Tregs, monocytes, and dendritic cells (DCs) were found mainly enriched in TMB-high samples.

Immunomodulatory Precision: A Narrative Review Exploring the Critical Role of Immune Checkpoint Inhibitors in Cancer Treatment

An immune checkpoint is a signaling pathway that regulates the recognition of antigens by T-cell receptors (TCRs) during an immune response. These checkpoints play a pivotal role in suppressing excessive immune responses and maintaining immune homeostasis against viral or microbial infections. There are several FDA-approved immune checkpoint inhibitors (ICIs), including ipilimumab, pembrolizumab, and avelumab. These ICIs target cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), programmed cell death protein 1 (PD-1), and programmed death ligand 1 (PD-L1). Furthermore, ongoing efforts are focused on developing new ICIs with emerging potential. In comparison to conventional treatments, ICIs offer the advantages of reduced side effects and durable responses. There is growing interest in the potential of combining different ICIs with chemotherapy, radiation therapy, or targeted therapies. This article comprehensively reviews the classification, mechanism of action, application, and combination strategies of ICIs in various cancers and discusses their current limitations. Our objective is to contribute to the future development of more effective anticancer drugs targeting immune checkpoints.

Facts and Hopes in Immunotherapy Strategies Targeting Antigens Derived from KRAS Mutations

In this commentary, we advance the notion that mutant KRAS (mKRAS) is an ideal tumor neoantigen that is amenable for targeting by the adaptive immune system. Recent progress highlights key advances on various fronts that validate mKRAS as a molecular target and support further pursuit as an immunological target. Because mKRAS is an intracellular membrane localized protein and not normally expressed on the cell surface, we surmise that proteasome degradation will generate short peptides that bind to HLA class I (HLA-I) molecules in the endoplasmic reticulum for transport through the Golgi for display on the cell surface. T-cell receptors (TCR)αβ and antibodies have been isolated that specifically recognize mKRAS encoded epitope(s) or haptenated-mKRAS peptides in the context of HLA-I on tumor cells. Case reports using adoptive T-cell therapy provide proof of principle that KRAS G12D can be successfully targeted by the immune system in patients with cancer. Among the challenges facing investigators is the requirement of precision medicine to identify and match patients to available mKRAS peptide/HLA therapeutics and to increase the population coverage by targeting additional mKRAS epitopes. Ultimately, we envision mKRAS-directed immunotherapy as an effective treatment option for selected patients that will complement and perhaps synergize with small-molecule mKRAS inhibitors and targeted mKRAS degraders.

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.

Efficacy of Pembrolizumab vs. Nivolumab Plus Ipilimumab in Metastatic NSCLC in Relation to PD-L1 and TMB Status

The efficacy of immune checkpoint inhibitor (ICI) therapy concerning programmed death ligand 1 (PD-L1) status is well established in patients diagnosed with non-small cell lung cancer (NSCLC). However, there remains a paucity of evidence regarding the efficacy concerning tumor mutational burden (TMB) in both clinical trials and real-world data (RWD). In the current article, clinicopathological and molecular epidemiological data were meticulously collected, and treatment modalities were meticulously recorded. The final analysis included a study population of 194 patients. Median age was 67 years (range 37-86), with the majority being male (71.13%), and 85.71% of patients were either current or former smokers at diagnosis. Adenocarcinoma accounted for most diagnoses (71.65%), followed by squamous cell carcinoma (24.23%). In terms of PD-L1 status, 42.78% had an expression level below 1%, 28.35% had an expression between 1-49%, and 28.87% had an expression above 50%. The TMB ranged from 0 to 75, with a median of 10.31 (range 0-75) for PD-L1 expression below 1%, with a median of 9.73 (range 0.95-39.63) for PD-L1 expression between 1-49%, and a median of 9.72 (range 0.95-48) for PD-L1 expression above 50%. Corresponding to patients with low PDL-1 less than 1% and low TMB (0-5), the median overall survival (mOS) was 16 (p = 0.18), and 15 months (p = 0.22), patients with medium PDL-1 (1-49%) and medium TMB (5-10), the mOS was 15 (p = 0.18) and 16 months (p = 0.22), patients with high PDL-1 (>50) and high TMB (>10), the mOS was 24 (p = 0.18) and 21 (p = 0.22) months. This study represents the largest academic RWD dataset concerning PD-L1 and TMB status in patients with locally advanced and metastatic NSCLC.

Molecular Heterogeneity in Leiomyosarcoma and Implications for Personalised Medicine

OPINION STATEMENT

Leiomyosarcoma (LMS) is one of the more common subtypes of soft tissue sarcomas (STS), accounting for about 20% of cases. Differences in anatomical location, risk of recurrence and histomorphological variants contribute to the substantial clinical heterogeneity in survival outcomes and therapy responses observed in patients. There is therefore a need to move away from the current one-size-fits-all treatment approach towards a personalised strategy tailored for individual patients. Over the past decade, tissue profiling studies have revealed key genomic features and an additional layer of molecular heterogeneity among patients, with potential utility for optimal risk stratification and biomarker-matched therapies. Furthermore, recent studies investigating intratumour heterogeneity and tumour evolution patterns in LMS suggest some key features that may need to be taken into consideration when designing treatment strategies and clinical trials. Moving forward, national and international collaborative efforts to aggregate expertise, data, resources and tools are needed to achieve a step change in improving patient survival outcomes in this disease of unmet need.

Identification and verification of a PANoptosis-related long noncoding ribonucleic acid signature for predicting the clinical outcomes and immune landscape in lung adenocarcinoma

PANoptosis is a type of programmed cell death (PCD) characterised by apoptosis, necroptosis and pyroptosis. Long non-coding ribonucleic acids (lncRNAs) are participating in the malignant behaviour of tumours regulated by PCD. Nevertheless, the function of PANoptosis-associated lncRNAs in lung adenocarcinoma remains to be investigated. In this work, a PANoptosis-related lncRNA signature (PRLSig) was developed based on the least absolute shrinkage and selection operator algorithm. The stability and fitness of PRLSig were confirmed by systematic evaluation of Kaplan-Meier, Cox analysis algorithm, receiver operating characteristic analysis, stratification analysis. In addition, ESTIMATE, single sample gene set enrichment analysis, immune checkpoints and the cancer immunome database confirmed the predictive value of the PRLSig in immune microenvironment and helped to identify populations for which immunotherapy is advantageous. The present research provides novel insights to facilitate risk stratification and optimise personalised treatment for LUAD.

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.

Mutation of neurotrophic tyrosine receptor kinase can promote pan-cancer immunity and the efficacy of immunotherapy

The Neurotrophic tyrosine receptor kinase (NTRK) family plays important roles in tumor progression and is involved in tumor immunogenicity. Here, we conducted a comprehensive bioinformatic and clinical analysis to investigate the characteristics of NTRK mutations and their association with the outcomes in pan-cancer immunotherapy. In 3888 patients across 12 cancer types, patients with NTRK-mutant tumors showed more benefit from immunotherapy in terms of objective response rate (ORR; 41.7% vs. 27.5%; P < 0.001), progress-free survival (PFS; HR = 0.80; 95% CI, 0.68-0.96; P = 0.01), and overall survival (OS; HR = 0.71; 95% CI, 0.61-0.82; P < 0.001). We further constructed and validated a nomogram to estimate survival probabilities after the initiation of immunotherapy. Multi-omics analysis on intrinsic and extrinsic immune landscapes indicated that NTRK mutation was associated with enhanced tumor immunogenicity, enriched infiltration of immune cells, and improved immune responses. In summary, NTRK mutation may promote cancer immunity and indicate favorable outcomes in immunotherapy. Our results have implications for treatment decision-making and developing immunotherapy for personalized care.

Multimodal Treatment of Metastatic Rectal Cancer in a Young Patient: Case Report and Literature Review

Metastatic colorectal cancer requires a multidisciplinary and individualized approach. Herein, we reported the case of a young woman diagnosed with metastatic rectal cancer who received an individualized multimodal treatment strategy that resulted in a remarkable survival. There were several particular aspects of this case, such as the early onset of the disease, the successful use of conversion therapy, the application of liquid biopsy to guide treatment, and the specific nature of the bone metastasis. To offer more insights for navigating such challenges in patients with metastatic colorectal cancer, we have conducted a literature review to find more data related to the particularities of this case. The incidence of early onset colorectal cancer is on the rise. Data suggests that it differs from older-onset colorectal cancer in terms of its pathological, epidemiological, anatomical, metabolic, and biological characteristics. Conversion therapy and surgical intervention provide an opportunity for cure and improve outcomes in metastatic colorectal cancer. It is important to approach each case individually, as every patient with limited liver disease should be considered as a candidate for secondary resection. Moreover, liquid biopsy has an important role in the individualized management of metastatic colorectal cancer patients, as it offers additional information for treatment decisions.

Identification and verification of AK4 as a protective immune-related biomarker in adipose-derived stem cells and breast cancer

Background

Breast cancer (BC) remains the most common cancer among women, and novel post-surgical reconstruction techniques, including autologous fat transplantation, have emerged. While Adipose-derived stem cells (ADSCs) are known to impact the viability of fat grafts, their influence on breast cancer progression remains unclear. This study aims to elucidate the genetic interplay between ADSCs and breast cancer, focusing on potential therapeutic targets.

Methods

Using the GEO and TCGA databases, we pinpointed differentially expressed (DE) mRNAs, miRNAs, lncRNAs, and pseudogenes of ADSCs and BC. We performed functional enrichment analysis and constructed protein-protein interaction (PPI), RNA binding protein (RBP)-pseudogene-mRNA, and lncRNA-miRNA-transcription factor (TF)-gene networks. Our study delved into the correlation of AK4 expression with 33 different malignancies and examined its impact on prognostic outcomes across a pan-cancer cohort. Additionally, we scrutinized immune infiltration, microsatellite instability, and tumor mutational burden, and conducted single-cell analysis to further understand the implications of AK4 expression. We identified novel sample subtypes based on hub genes using the ConsensusClusterPlus package and examined their association with immune infiltration. The random forest algorithm was used to screen DE mRNAs between subtypes to validate the powerful prognostic prediction ability of the artificial neural network.

Results

Our analysis identified 395 DE mRNAs, 3 DE miRNAs, 84 DE lncRNAs, and 26 DE pseudogenes associated with ADSCs and BC. Of these, 173 mRNAs were commonly regulated in both ADSCs and breast cancer, and 222 exhibited differential regulation. The PPI, RBP-pseudogene-mRNA, and lncRNA-miRNA-TF-gene networks suggested AK4 as a key regulator. Our findings support AK4 as a promising immune-related therapeutic target for a wide range of malignancies. We identified 14 characteristic genes based on the AK4-related cluster using the random forest algorithm. Our artificial neural network yielded excellent diagnostic performance in the testing cohort with AUC values of 0.994, 0.973, and 0.995, indicating its ability to distinguish between breast cancer and non-breast cancer cases.

Conclusions

Our research sheds light on the dual role of ADSCs in BC at the genetic level and identifies AK4 as a key protective mRNA in breast cancer. We found that AK4 significantly predicts cancer prognosis and immunotherapy, indicating its potential as a therapeutic target.

Development and validation of an interpretable radiomic signature for preoperative estimation of tumor mutational burden in lung adenocarcinoma

Background

Tumor mutational burden (TMB) is a promising biomarker for immunotherapy. The challenge of spatial and temporal heterogeneity and high costs weaken its power in clinical routine. The aim of this study is to estimate TMB preoperatively using a volumetric CT-based radiomic signature (rMB).

Methods

Seventy-one patients with resectable lung adenocarcinoma (LUAD) who underwent whole-exome sequencing (WXS) from 2011 to 2014 were enrolled from the institutional biobank of Tianjin Medical University Cancer Institute and Hospital (TMUCIH). Forty-nine LUAD patients with WXS from the Cancer Genome Atlas Program (TCGA) served as the external validation cohort. Computed tomography (CT) volumes were resampled to 1-mm isotropic, semi-automatically segmented, and manually adjusted by two radiologists. A total of 3,108 radiomic features were extracted via PyRadiomics and then harmonized across cohorts by ComBat. Features with inter-segmentation intra-class correlation coefficient (ICC) > 0.8, low collinearity, and significant univariate power were passed to the least absolute shrinkage and selection operator (LASSO)-logistic classifier to discriminate TMB-high/TMB-low at a threshold of 10 mut/Mb. The receiver operating characteristic (ROC) curve analysis and calibration curve were used to determine its efficiency. Shapley values (SHAP) attributed individual predictions to feature contributions. Clinical variables and circulating biomarkers were collected to find potential associations with TMB and rMB.

Results

The top frequently mutated genes significantly differed between the Chinese and TCGA cohorts, with a median TMB of 2.20 and 3.46 mut/Mb and 15 (21.12%) and 9 (18.37%) cases of TMB-high, respectively. After dimensionality reduction, rMB comprised 21 features, which reached an AUC of 0.895 (sensitivity = 0.867, specificity = 0.875, and accuracy = 0.873) in the discovery cohort and 0.878 (sensitivity = 1.0, specificity = 0.825, and accuracy = 0.857 in a consist cutoff) in the validation cohort. rMB of TMB-high patients was significantly higher than rMB of TMB-low patients in both cohorts (p < 0.01). rMB was well-calibrated in the discovery cohort and validation cohort (p = 0.27 and 0.74, respectively). The square-filtered gray-level concurrence matrix (GLCM) correlation was of significant importance in prediction. The proportion of circulating monocytes and the monocyte-to-lymphocyte ratio were associated with TMB, whereas the circulating neutrophils and lymphocyte percentage, original and derived neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio were associated with rMB.

Conclusion

rMB, an intra-tumor radiomic signature, could predict lung adenocarcinoma patients with higher TMB. Insights from the Shapley values may enhance persuasiveness of the purposed signature for further clinical application. rMB could become a promising tool to triage patients who might benefit from a next-generation sequencing test.

Association of CCND1 rs9344 polymorphism with lung cancer susceptibility and clinical outcomes: a case-control study

BACKGROUND

Cyclin D1 (CCND1) plays a pivotal role in cancer susceptibility and the platinum-based chemotherapy response. This study aims to assess the relationship between a common polymorphism (rs9344 G > A) in CCND1 gene with cancer susceptibility, platinum-based chemotherapy response, toxicities and prognosis of patients with lung cancer.

METHODS

This study involved 498 lung cancer patients and 213 healthy controls. Among them, 467 patients received at least two cycles of platinum-based chemotherapy. Unconditional logistical regression analysis and meta-analysis were performed to evaluate the associations.

RESULTS

The lung adenocarcinoma risk was significantly higher in patients with AA than GG + GA genotype (adjusted OR = 1.755, 95%CI = 1.057-2.912, P = 0.030). CCND1 rs9344 was significantly correlated with platinum-based therapy response in patients receiving PP regimen (additive model: adjusted OR = 1.926, 95%CI = 1.029-3.605, P = 0.040; recessive model: adjusted OR = 11.340, 95%CI = 1.428-90.100, P = 0.022) and in the ADC subgroups (recessive model: adjusted OR = 3.345, 95%CI = 1.276-8.765, P = 0.014). Furthermore, an increased risk of overall toxicity was found in NSCLC patients (additive model: adjusted OR = 1.395, 95%CI = 1.025-1.897, P = 0.034; recessive model: adjusted OR = 1.852, 95%CI = 1.088-3.152, P = 0.023), especially ADC subgroups (additive model: adjusted OR = 1.547, 95%CI = 1.015-2.359, P = 0.043; recessive model: adjusted OR = 2.030, 95%CI = 1.017-4.052, P = 0.045). Additionally, CCND1 rs9344 was associated with an increased risk of gastrointestinal toxicity in non-smokers (recessive model: adjusted OR = 2.620, 95%CI = 1.083-6.336, P = 0.035). Non-significant differences were observed in the 5-year overall survival rate between CCND1 rs9344 genotypes. A meta-analysis of 5432 cases and 6452 control samples did not find a significant association between lung cancer risk and CCND1 rs9344 polymorphism.

CONCLUSION

This study suggests that in the Chinese population, CCND1 rs9344 could potentially serve as a candidate biomarker for cancer susceptibility and treatment outcomes in specific subgroups of patients.

Tumor mutational burden for the prediction of PD-(L)1 blockade efficacy in cancer: challenges and opportunities

Tumor mutational burden (TMB) is a biomarker that measures the number of somatic mutations in a tumor's genome. TMB has emerged as a predictor of response to immune checkpoint inhibitors (ICIs) in various cancer types, and several studies have shown that patients with high TMB have better outcomes when treated with programmed death-ligand 1-based therapies. Recently, the Food and Drug Administration has approved TMB as a companion diagnostic for the use of pembrolizumab in solid tumors. However, despite its potential, the use of TMB as a biomarker for immunotherapy efficacy is limited by several factors. Here we review the limitations of TMB in predicting immunotherapy outcomes in patients with cancer and discuss potential strategies to optimize its use in the clinic.

Immune Cytolytic Activity and Strategies for Therapeutic Treatment

Intratumoral immune cytolytic activity (CYT), calculated as the geometric mean of granzyme-A (GZMA) and perforin-1 (PRF1) expression, has emerged as a critical factor in cancer immunotherapy, with significant implications for patient prognosis and treatment outcomes. Immune checkpoint pathways, the composition of the tumor microenvironment (TME), antigen presentation, and metabolic pathways regulate CYT. Here, we describe the various methods with which we can assess CYT. The detection and analysis of tumor-infiltrating lymphocytes (TILs) using flow cytometry or immunohistochemistry provide important information about immune cell populations within the TME. Gene expression profiling and spatial analysis techniques, such as multiplex immunofluorescence and imaging mass cytometry allow the study of CYT in the context of the TME. We discuss the significant clinical implications that CYT has, as its increased levels are associated with positive clinical outcomes and a favorable prognosis. Moreover, CYT can be used as a prognostic biomarker and aid in patient stratification. Altering CYT through the different methods targeting it, offers promising paths for improving treatment responses. Overall, understanding and modulating CYT is critical for improving cancer immunotherapy. Research into CYT and the factors that influence it has the potential to transform cancer treatment and improve patient outcomes.

Analysis of tumor mutational burden and mutational landscape comparing whole-exome sequencing and comprehensive genomic profiling in patients with resectable early-stage non-small-cell lung cancer

Background

Identifying actionable driver mutations via tissue-based comprehensive genomic profiling (CGP) is paramount in treatment decisions for metastatic non-squamous, non-small-cell lung cancer (NSCLC). However, the role of CGP remains elusive in resectable NSCLC. Here, we elucidate the feasibility of CGP in early-stage NSCLC Korean patients and compare the tumor mutational burden (TMB) and mutation landscape using three different platforms.

Methods

All surgically resected NSCLC samples (N = 96) were analyzed to assess the concordance in TMB calculation and targetable mutations using whole-exome sequencing (WES) and TruSight Oncology 500 (TSO500). In all, 26 samples were analyzed with Foundation One CDx Assay (F1CDx). Programmed death-ligand 1 (PD-L1) expression was evaluated using Vectra Polaris.

Results

Stage distribution post-surgery was 80% I (N = 77) and 20% II (N = 19). Ninety-nine percent (N = 95) were adenocarcinoma. The median TMB with WES and TSO500 was 1.6 and 4.7 mut/Mb, respectively (p < 0.05). Using all three platforms, the median TMB was 1.9, 5.5, and 4 mut/Mb for WES, TSO500, and F1CDx, respectively (p = 0.0048). Linear regression analysis of TMB values calculated between WES and TSO500 resulted in a concordance correlation coefficient of 0.83. For the PD-L1 tumor proportion score of <1% (negative, N = 18), 1-49% (low, N = 68), and ⩾50% (high, N = 10), the R2 values were 0.075, 0.79, and 0.95, respectively. The R2 values for TMB concordance were variable between the three platforms. Mutation landscape revealed EGFR mutation (51%, N = 49) as the most common actionable driver mutation, comprising L858R (N = 22), E19del (N = 20), and other non-common EGFR mutations (N = 7).

Conclusion

TSO500 and F1CDx showed robust analytical performance for TMB assessment with TSO500 showing stronger concordance of TMB with high PD-L1 expression. As the paradigm for the management of early-resected NSCLC continues to evolve, understanding TMB and the mutation landscape may help advance clinical outcomes for this subset of patients.

Tertiary lymphoid structures and B cells determine clinically relevant T cell phenotypes in ovarian cancer

Intratumoral tertiary lymphoid structures (TLSs) have been associated with improved outcome in various cohorts of patients with cancer, reflecting their contribution to the development of tumor-targeting immunity. Here, we demonstrate that high-grade serous ovarian carcinoma (HGSOC) contains distinct immune aggregates with varying degrees of organization and maturation. Specifically, mature TLSs (mTLS) as forming only in 16% of HGSOCs with relatively elevated tumor mutational burden (TMB) are associated with an increased intratumoral density of CD8+ effector T (TEFF) cells and TIM3+PD1+, hence poorly immune checkpoint inhibitor (ICI)-sensitive, CD8+ T cells. Conversely, CD8+ T cells from immunologically hot tumors like non-small cell lung carcinoma (NSCLC) are enriched in ICI-responsive TCF1+ PD1+ T cells. Spatial B-cell profiling identifies patterns of in situ maturation and differentiation associated with mTLSs. Moreover, B-cell depletion promotes signs of a dysfunctional CD8+ T cell compartment among tumor-infiltrating lymphocytes from freshly isolated HGSOC and NSCLC biopsies. Taken together, our data demonstrate that - at odds with NSCLC - HGSOC is associated with a low density of follicular helper T cells and thus develops a limited number of mTLS that might be insufficient to preserve a ICI-sensitive TCF1+PD1+ CD8+ T cell phenotype. These findings point to key quantitative and qualitative differences between mTLSs in ICI-responsive vs ICI-irresponsive neoplasms that may guide the development of alternative immunotherapies for patients with HGSOC.

Pan-cancer analysis of NUP155 and validation of its role in breast cancer cell proliferation, migration, and apoptosis

NUP155 is reported to be correlated with tumor development. However, the role of NUP155 in tumor physiology and the tumor immune microenvironment (TIME) has not been previously examined. This study comprehensively investigated the expression, immunological function, and prognostic significance of NUP155 in different cancer types. Bioinformatics analysis revealed that NUP155 was upregulated in 26 types of cancer. Additionally, NUP155 upregulation was strongly correlated with advanced pathological or clinical stages and poor prognosis in several cancers. Furthermore, NUP155 was significantly and positively correlated with DNA methylation, tumor mutational burden, microsatellite instability, and stemness score in most cancers. Additionally, NUP155 was also found to be involved in TIME and closely associated with tumor infiltrating immune cells and immunoregulation-related genes. Functional enrichment analysis revealed a strong correlation between NUP155 and immunomodulatory pathways, especially antigen processing and presentation. The role of NUP155 in breast cancer has not been examined. This study, for the first time, demonstrated that NUP155 was upregulated in breast invasive carcinoma (BRCA) cells and revealed its oncogenic role in BRCA using molecular biology experiments. Thus, our study highlights the potential value of NUP155 as a biomarker in the assessment of prognostic prediction, tumor microenvironment and immunotherapeutic response in pan-cancer.

Phase II study of nivolumab in patients with genetic alterations in DNA damage repair and response who progressed after standard treatment for metastatic solid cancers (KM-06)

BACKGROUND

Immune-modulating antibodies targeting programmed cell death protein 1/programmed death-ligand 1 (PD-1/PD-L1) have demonstrated promising antitumor efficacy in various types of cancers, especially highly mutated ones. Genetic alterations in DNA damage response and repair (DDR) genes can lead to genetic instability, often accompanied by a high tumor mutation burden (TMB). However, few studies have validated the aberration of DDR genes as a predictive biomarker for response to immune-modulating antibodies.

METHODS

The KM-06 open-label, multicenter, single-arm, phase II trial evaluated the safety and efficacy of nivolumab in refractory solid cancers with DDR gene mutations assessed by clinically targeted sequencing. Nivolumab (3 mg/kg) was administered every 2 weeks until disease progression, unacceptable toxicity, or for 24 months. The primary endpoint was the objective response rate (ORR) as per RECIST V.1.1 criteria.

RESULTS

A total of 48 patients were enrolled in the study (median age 61, 58.3% male). The most common cancer type was colorectal cancer (41.7%), followed by prostate and biliary tract cancer (8.3% each). Eight patients achieved a partial response as their best overall response, resulting in an ORR of 17.8%. The disease control rate was 60.0%. The median progression-free survival was 2.9 months. Treatment-related adverse events of any grade and grade ≥3 occurred in 44 (91.7%) and 4 (8.3%) patients, respectively. Clinically targeted sequencing data inferred both TMB and microsatellite instability (MSI). Using a TMB cut-off of 12 mut/Mb, there were significant differences in overall survival (p=0.00035), progression-free survival (p=0.0061), and the best overall response (p=0.05). In the RNA sequencing analysis, nivolumab responders showed activation of the interleukin signaling pathway. Patients who experienced early progression presented high epithelial-mesenchymal transition signaling pathway activation. The responders exhibited a marked increase in PD-1-/Ki67+CD8 T cells at the early stage of treatment (C3D1) compared with non-responders (p=0.03).

CONCLUSIONS

In this phase II trial, nivolumab demonstrated moderate efficacy and manageable toxicity in patients with solid cancer harboring DDR gene mutations. A high TMB (>12 mut/Mb) and MSI score (>2.5) determined through clinically target sequencing presented significant discriminatory power for the nivolumab response.

TRIAL REGISTRATION NUMBER

NCT04761744.

Comprehensive analysis of a NAD+ metabolism-derived gene signature to predict the prognosis and immune landscape in endometrial cancer

As a crucial regulator influencing tumor progression, nicotinamide adenine dinucleotide (NAD+) is widely acknowledged. However, its role in endometrial cancer (EC) is not completely understood. In this study, we aimed to develop an NAD+metabolic-related genes (NMRGs) risk signature that could reflect the prognosis of EC patients and their responsiveness to immunotherapy and chemotherapy. Data from The Cancer Genome Atlas (TCGA) databases and the Molecular Signatures Database (MSigDB) confirmed two distinct NMRG subtypes in EC patients using consensus clustering, and a risk score was constructed utilizing an NAD+-related prognostic signature depending on the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Receiver operating characteristic (ROC) curves were employed to assess the model's precision. Additionally, we used Gene Set Enrichment Analysis (GSEA) to predict the biological signaling pathways that might be involved. We also explored the role of the risk score in immune cell infiltration, tumor mutation burden (TMB), immunotherapy, and chemotherapy. Our study established a prognostic risk signature based on six NMRGs, and we observed that the high-risk group was associated with a poorer prognosis. Furthermore, we identified a strong correlation between the high-risk group and several pathways, including DNA replication, cell cycle, and mismatch repair. Lastly, our findings highlighted the influence of NMRGs on the regulation of immune infiltration in EC. Therefore, this signature holds potential value in predicting the prognosis of EC patients and guiding their management, including decisions regarding immunotherapy and chemotherapy, ultimately improving the accuracy of EC patient care.

Long-read sequencing unveils novel somatic variants and methylation patterns in the genetic information system of early lung cancer

Lung cancer poses a global health challenge, necessitating advanced diagnostics for improved outcomes. Intensive efforts are ongoing to pinpoint early detection biomarkers, such as genomic variations and DNA methylation, to elevate diagnostic precision. We conducted long-read sequencing on cancerous and adjacent non-cancerous tissues from a patient with lung adenocarcinoma. We identified somatic structural variations (SVs) specific to lung cancer by integrating data from various SV calling methods and differentially methylated regions (DMRs) that were distinct between these two tissue samples, revealing a unique methylation pattern associated with lung cancer. This study discovered over 40,000 somatic SVs and over 180,000 DMRs linked to lung cancer. We identified approximately 700 genes of significant relevance through comprehensive analysis, including genes intricately associated with many lung cancers, such as NOTCH1, SMOC2, CSMD2, and others. Furthermore, we observed that somatic SVs and DMRs were substantially enriched in several pathways, such as axon guidance signaling pathways, which suggests a comprehensive multi-omics impact on lung cancer progression across various biological investigation levels. These datasets can potentially serve as biomarkers for early lung cancer detection and may hold significant value in clinical diagnosis and treatment applications.

Spatial Relationships in the Tumor Microenvironment Demonstrate Association with Pathologic Response to Neoadjuvant Chemoimmunotherapy in Muscle-invasive Bladder Cancer

BACKGROUND

Platinum-based neoadjuvant chemotherapy (NAC) is standard for patients with muscle-invasive bladder cancer (MIBC). Pathologic response (complete: ypT0N0 and partial:

OBJECTIVE

Using the NanoString GeoMx platform, we performed proteomic digital spatial profiling (DSP) on transurethral resections of bladder tumors from 18 responders (

DESIGN, SETTING, AND PARTICIPANTS

Pretreatment tumor samples were stained by hematoxylin and eosin and immunofluorescence (panCK and CD45) to select four regions of interest (ROIs): tumor enriched (TE), immune enriched (IE), tumor/immune interface (tumor interface = TX and immune interface = IX).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

DSP was performed with 52 protein markers from immune cell profiling, immunotherapy drug target, immune activation status, immune cell typing, and pan-tumor panels.

RESULTS AND LIMITATIONS

Protein marker expression patterns were analyzed to determine their association with pathologic response, incorporating or agnostic of their ROI designation (TE/IE/TX/IX). Overall, DSP-based marker expression showed high intratumoral heterogeneity; however, response was associated with markers including PD-L1 (ROI agnostic), Ki-67 (ROI agnostic, TE, IE, and TX), HLA-DR (TX), and HER2 (TE). An elastic net model of response with ROI-inclusive markers demonstrated better validation set performance (area under the curve [AUC] = 0.827) than an ROI-agnostic model (AUC = 0.432). A model including DSP, tumor mutational burden, and clinical data performed no better (AUC = 0.821) than the DSP-only model.

CONCLUSIONS

Despite high intratumoral heterogeneity of DSP-based marker expression, we observed associations between pathologic response and specific DSP-based markers in a spatially dependent context. Further exploration of tumor region-specific biomarkers may help predict response to neoadjuvant chemoimmunotherapy in MIBC.

PATIENT SUMMARY

In this study, we used the GeoMx platform to perform proteomic digital spatial profiling on transurethral resections of bladder tumors from 18 responders and 18 nonresponders from two studies of neoadjuvant chemotherapy (gemcitabine and cisplatin) plus immune checkpoint inhibitor therapy (LCCC1520 [pembrolizumab] and BLASST-1 [nivolumab]). We found that assessing protein marker expression in the context of tumor architecture improved response prediction.

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Key Words

• BLASST-1
• Bladder cancer
• Digital spatial profiling
• Elastic net regression
• GeoMx
• LCCC1520
• Neoadjuvant chemoimmunotherapy

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MESH Headings

• Humans
• Cisplatin
• Neoadjuvant Therapy/methods
• Gemcitabine
• Nivolumab/therapeutic use
• Proteomics
• Tumor Microenvironment
• Urinary Bladder Neoplasms/drug therapy
• Urinary Bladder Neoplasms/pathology
• Biomarkers, Tumor
• Muscles/pathology
• Immunotherapy
• Neoplasm Invasiveness
• Cystectomy

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Grants

• P30 CA016086 NCI NIH HHS
• R01 CA241810 NCI NIH HHS
• T32 CA244125 NCI NIH HHS

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Affiliation(s)

Wolfgang Beckabir Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Microbiology and Immunology, UNC School of Medicine, Chapel Hill, NC, USA
Sara E Wobker Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Pathology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Jeffrey S Damrauer Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Division of Oncology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Bentley Midkiff Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Gabriela De la Cruz Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Vladmir Makarov Department of Hematology and Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH, USA
Leah Flick Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Mark G Woodcock Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Microbiology and Immunology, UNC School of Medicine, Chapel Hill, NC, USA
Petros Grivas Department of Medicine, Division of Medical Oncology, University of Washington, Fred Hutchinson Cancer Center, Seattle, WA, USA
Marc A Bjurlin Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Urology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Michael R Harrison Division of Medical Oncology, Department of Medicine, Duke Cancer Institute, Duke University, Durham, NC, USA
Benjamin G Vincent Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Microbiology and Immunology, UNC School of Medicine, Chapel Hill, NC, USA; Division of Hematology, Department of Medicine, UNC School of Medicine, Chapel Hill, NC, USA; Computational Medicine Program, UNC School of Medicine, Chapel Hill, NC, USA; Curriculum in Bioinformatics and Computational Biology, UNC School of Medicine, Chapel Hill, NC, USA
Tracy L Rose Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Division of Oncology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Shilpa Gupta Department of Hematology and Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH, USA
William Y Kim Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Division of Oncology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Matthew I Milowsky Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Division of Oncology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

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